title stringlengths 21 128 | content_TLDR stringlengths 40 250 | abstract stringlengths 613 2.09k | authors listlengths 1 42 | openreview_url stringlengths 42 42 | id stringlengths 10 10 | forum stringlengths 10 10 | authorids listlengths 1 42 | venue dict | venueid dict | pdf_url dict | invitation stringclasses 1
value | group stringclasses 1
value | venue_name stringclasses 1
value | year int64 2.03k 2.03k | conference stringclasses 1
value | content_keywords listlengths 1 16 | content_code_of_ethics stringclasses 1
value | content_author_guide stringclasses 1
value | content_flagged_for_ethics_review bool 1
class | content_ethics_comments stringclasses 11
values | content__bibtex stringlengths 246 1.01k | content_paperhash stringlengths 29 134 | content_supplementary_material stringclasses 73
values | content_award_nomination bool 1
class | content_reciprocal_reviewing_status stringclasses 1
value | content_reciprocal_reviewing_author stringclasses 4
values | content_reciprocal_reviewing_exemption_reason dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources | Open-Qwen2VL is a fully open-source multimodal LLM which is trained on only 5B high-quality multimodal tokens but outperforms Qwen2-VL, trained on 1.4T tokens, on various benchmarks. | The reproduction of state-of-the-art multimodal LLM pre-training faces barriers at every stage of the pipeline, including high-quality data filtering, multimodal data mixture strategies, sequence packing techniques, and training frameworks. We introduce Open-Qwen2VL, a fully open-source 2B-parameter Multimodal Large La... | [
"Weizhi Wang",
"Yu Tian",
"Linjie Yang",
"Heng Wang",
"Xifeng Yan"
] | https://openreview.net/forum?id=nVQmW1af6j | nVQmW1af6j | nVQmW1af6j | [
"~Weizhi_Wang1",
"~Yu_Tian4",
"~Linjie_Yang4",
"~Heng_Wang2",
"~Xifeng_Yan1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ee174c9b1df40753c61805a156d2891016605052.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"multimodal large language model",
"efficient pre-training",
"high quality image-text filtering"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wang2025openqwenvl,
title={Open-Qwen2{VL}: Compute-Efficient Pre-Training of Fully-Open Multimodal {LLM}s on Academic Resources},
author={Weizhi Wang and Yu Tian and Linjie Yang and Heng Wang and Xifeng Yan},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/fo... | wang|openqwen2vl_computeefficient_pretraining_of_fullyopen_multimodal_llms_on_academic_resources | null | null | null | null | null | |
Plancraft: an evaluation dataset for planning with LLM agents | We introduce Plancraft, a multi-modal evaluation dataset for LLMs, designed to assess tool use, planning, and decision-making with both solvable and unsolvable examples. | We present Plancraft, a multi-modal evaluation dataset for LLM agents. Plancraft has both a text-only and multi-modal interface, based on the Minecraft crafting GUI. We include the Minecraft Wiki to evaluate tool use and Retrieval Augmented Generation (RAG), as well as a handcrafted planner and Oracle Retriever, to abl... | [
"Gautier Dagan",
"Frank Keller",
"Alex Lascarides"
] | https://openreview.net/forum?id=nSV8Depcpx | nSV8Depcpx | nSV8Depcpx | [
"~Gautier_Dagan1",
"~Frank_Keller1",
"~Alex_Lascarides1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/9dbb6b20cff2ad8aca8728850e46fd135d8a2353.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"planning",
"multi-modal",
"agents",
"LLMs",
"tool use",
"minecraft",
"RAG"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
dagan2025plancraft,
title={Plancraft: an evaluation dataset for planning with {LLM} agents},
author={Gautier Dagan and Frank Keller and Alex Lascarides},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=nSV8Depcpx}
} | dagan|plancraft_an_evaluation_dataset_for_planning_with_llm_agents | /attachment/73266a3ae8ba8b61a11ec99084fc33ef47b66c57.zip | null | null | null | null | |
Teaching Models to Understand (but not Generate) High-risk Data | A new pre-training paradigm that enables language models to understand high-risk data without learning to generate it. | Language model developers typically filter out high-risk content—such as toxic or copyrighted text—from their pre-training data to prevent models from generating similar outputs. However, removing such data altogether limits models’ ability to recognize and appropriately respond to harmful or sensitive content. In this... | [
"Ryan Yixiang Wang",
"Matthew Finlayson",
"Luca Soldaini",
"Swabha Swayamdipta",
"Robin Jia"
] | https://openreview.net/forum?id=n6mTO5JS4j | n6mTO5JS4j | n6mTO5JS4j | [
"~Ryan_Yixiang_Wang1",
"~Matthew_Finlayson1",
"~Luca_Soldaini1",
"~Swabha_Swayamdipta1",
"~Robin_Jia1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/4c4b33c1dca8f5ac130e0bc60c949aed1976381b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLMs",
"Language Models",
"Pre-training Data"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wang2025teaching,
title={Teaching Models to Understand (but not Generate) High-risk Data},
author={Ryan Yixiang Wang and Matthew Finlayson and Luca Soldaini and Swabha Swayamdipta and Robin Jia},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=n6mTO5... | wang|teaching_models_to_understand_but_not_generate_highrisk_data | null | null | null | null | null | |
Defending LLM Watermarking Against Spoofing Attacks with Contrastive Representation Learning | The paper proposes a semantic-aware watermarking method that defends against spoofing attacks by using a contrastively trained semantic mapping model to detect semantic distortions. | Watermarking has emerged as a promising technique for detecting texts generated by LLMs. Current research has primarily focused on three design criteria -- high quality of the watermarked text, high detectability, and robustness against removal attack. However, the security against spoofing attacks remains relatively u... | [
"Li An",
"Yujian Liu",
"Yepeng Liu",
"Yang Zhang",
"Yuheng Bu",
"Shiyu Chang"
] | https://openreview.net/forum?id=n5hmtkdl7k | n5hmtkdl7k | n5hmtkdl7k | [
"~Li_An3",
"~Yujian_Liu1",
"~Yepeng_Liu1",
"~Yang_Zhang3",
"~Yuheng_Bu1",
"~Shiyu_Chang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/3244e3dcdb7ec5c678906e32428bd780da24db80.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM watermarking",
"Spoofing attack",
"Piggyback Spoofing attack"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
an2025defending,
title={Defending {LLM} Watermarking Against Spoofing Attacks with Contrastive Representation Learning},
author={Li An and Yujian Liu and Yepeng Liu and Yang Zhang and Yuheng Bu and Shiyu Chang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net... | an|defending_llm_watermarking_against_spoofing_attacks_with_contrastive_representation_learning | null | null | null | null | null | |
True Multimodal In-Context Learning Needs Attention to the Visual Context | We propose both a Dynamic Attention Reallocation tuning algorithm and a dedicated dataset to improve the true MICL ability of MLLMs | Multimodal Large Language Models (MLLMs), built on powerful language backbones, have enabled Multimodal In-Context Learning (MICL)—adapting to new tasks from a few multimodal demonstrations consisting of images, questions, and answers.
Despite showing noticeable improvement on standard vision-language datasets, current... | [
"Shuo Chen",
"Jianzhe Liu",
"Zhen Han",
"Yan Xia",
"Daniel Cremers",
"Philip Torr",
"Volker Tresp",
"Jindong Gu"
] | https://openreview.net/forum?id=n4JdyBGu6T | n4JdyBGu6T | n4JdyBGu6T | [
"~Shuo_Chen12",
"~Jianzhe_Liu1",
"~Zhen_Han3",
"~Yan_Xia5",
"~Daniel_Cremers1",
"~Philip_Torr1",
"~Volker_Tresp1",
"~Jindong_Gu1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/da3367f29bfb2c448b1ae58988478c487bd06b7c.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Multimodal In-Context Learning",
"Multimodal Large Language Models",
"Vision Language Models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
chen2025true,
title={True Multimodal In-Context Learning Needs Attention to the Visual Context},
author={Shuo Chen and Jianzhe Liu and Zhen Han and Yan Xia and Daniel Cremers and Philip Torr and Volker Tresp and Jindong Gu},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://o... | chen|true_multimodal_incontext_learning_needs_attention_to_the_visual_context | null | null | null | null | null | |
Mixture of Attention Spans: Optimizing LLM Inference Efficiency with Heterogeneous Sliding-Window Lengths | We design heterogeneous elastic rules for sliding-window lengths of attention for efficient large language models | Sliding-window attention offers a hardware-efficient solution to the memory and throughput challenges of Large Language Models (LLMs) in long-context scenarios. Existing methods typically employ a single window length across all attention heads and input sizes. However, this uniform approach fails to capture the hetero... | [
"Tianyu Fu",
"Haofeng Huang",
"Xuefei Ning",
"Genghan Zhang",
"Boju Chen",
"Tianqi Wu",
"Hongyi Wang",
"Zixiao Huang",
"Shiyao Li",
"Shengen Yan",
"Guohao Dai",
"Huazhong Yang",
"Yu Wang"
] | https://openreview.net/forum?id=n3rZJrWPLE | n3rZJrWPLE | n3rZJrWPLE | [
"~Tianyu_Fu3",
"~Haofeng_Huang3",
"~Xuefei_Ning1",
"~Genghan_Zhang1",
"~Boju_Chen1",
"~Tianqi_Wu2",
"~Hongyi_Wang8",
"~Zixiao_Huang2",
"~Shiyao_Li2",
"~Shengen_Yan1",
"~Guohao_Dai4",
"~Huazhong_Yang2",
"~Yu_Wang3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c9da10b21088f5f6d7b33ab09e49c617dd22c0c3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Efficient Attention",
"Sparse Attention",
"KV Cache Management",
"Large Language Models",
"Efficiency"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
fu2025mixture,
title={Mixture of Attention Spans: Optimizing {LLM} Inference Efficiency with Heterogeneous Sliding-Window Lengths},
author={Tianyu Fu and Haofeng Huang and Xuefei Ning and Genghan Zhang and Boju Chen and Tianqi Wu and Hongyi Wang and Zixiao Huang and Shiyao Li and Shengen Yan and Guohao ... | fu|mixture_of_attention_spans_optimizing_llm_inference_efficiency_with_heterogeneous_slidingwindow_lengths | null | null | null | null | null | |
Fluid Language Model Benchmarking | Fluid Benchmarking improves evaluation by adapting items to the capability level of language models. | Language model (LM) benchmarking faces several challenges: comprehensive evaluations are costly, benchmarks often fail to measure the intended capabilities, and evaluation quality can degrade due to labeling errors and benchmark saturation. Although various strategies have been proposed to mitigate these issues, they t... | [
"Valentin Hofmann",
"David Heineman",
"Ian Magnusson",
"Kyle Lo",
"Jesse Dodge",
"Maarten Sap",
"Pang Wei Koh",
"Chun Wang",
"Hannaneh Hajishirzi",
"Noah A. Smith"
] | https://openreview.net/forum?id=mxcCg9YRqj | mxcCg9YRqj | mxcCg9YRqj | [
"~Valentin_Hofmann1",
"~David_Heineman1",
"~Ian_Magnusson1",
"~Kyle_Lo1",
"~Jesse_Dodge1",
"~Maarten_Sap1",
"~Pang_Wei_Koh1",
"~Chun_Wang8",
"~Hannaneh_Hajishirzi1",
"~Noah_A._Smith2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/998cc5e4815d857cf1218ede711a4cc0e044ac3d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"language models",
"evaluation",
"item response theory",
"efficiency",
"robustness"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
hofmann2025fluid,
title={Fluid Language Model Benchmarking},
author={Valentin Hofmann and David Heineman and Ian Magnusson and Kyle Lo and Jesse Dodge and Maarten Sap and Pang Wei Koh and Chun Wang and Hannaneh Hajishirzi and Noah A. Smith},
booktitle={Second Conference on Language Modeling},
year={2025... | hofmann|fluid_language_model_benchmarking | null | true | This submission is NOT exempt from the Reciprocal Reviewing requirement. (We expect most submissions to fall in this category.) | ~Valentin_Hofmann1 | {
"readers": [
"colmweb.org/COLM/2025/Conference",
"colmweb.org/COLM/2025/Conference/Submission1586/Authors"
]
} | |
Rethinking Multilingual Continual Pretraining: Data Mixing for Adapting LLMs Across Languages and Resources | This study evaluates 36 continual pretraining configurations across three multilingual LLMs and 30+ languages, analyzing their effects across resource levels and language behavior categories. | Large Language Models (LLMs) exhibit significant disparities in performance across languages, primarily benefiting high-resource languages while marginalizing underrepresented ones. Continual Pretraining (CPT) has emerged as a promising approach to address this imbalance, although the relative effectiveness of monoling... | [
"Zihao Li",
"Shaoxiong Ji",
"Hengyu Luo",
"Jörg Tiedemann"
] | https://openreview.net/forum?id=mpTIzK4Zca | mpTIzK4Zca | mpTIzK4Zca | [
"~Zihao_Li13",
"~Shaoxiong_Ji1",
"~Hengyu_Luo1",
"~Jörg_Tiedemann1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/574bedec3f3e2b12092d3af357d15c9c990d9a65.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Multilingual continual pretraining",
"data mixing"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
li2025rethinking,
title={Rethinking Multilingual Continual Pretraining: Data Mixing for Adapting {LLM}s Across Languages and Resources},
author={Zihao Li and Shaoxiong Ji and Hengyu Luo and J{\"o}rg Tiedemann},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/... | li|rethinking_multilingual_continual_pretraining_data_mixing_for_adapting_llms_across_languages_and_resources | null | null | null | null | null | |
SPIN-Bench: How Well Do LLMs Plan Strategically and Reason Socially? | SPIN-Bench tests LLMs on strategic planning and social intelligence, showing they struggle with complex multi-agent scenarios requiring extended reasoning and negotiation. | Reasoning and strategic behavior in social interactions is a hallmark of intelligence. This form of reasoning is significantly more sophisticated than isolated planning or reasoning tasks in static settings (e.g., math problem solving). In this paper, we present Strategic Planning, Interaction, and Negotiation (SPIN-Be... | [
"Jianzhu Yao",
"Kevin Wang",
"Ryan Hsieh",
"Haisu Zhou",
"Tianqing Zou",
"Zerui Cheng",
"Zhangyang Wang",
"Pramod Viswanath"
] | https://openreview.net/forum?id=mgsS73kvOA | mgsS73kvOA | mgsS73kvOA | [
"~Jianzhu_Yao1",
"~Kevin_Wang4",
"~Ryan_Hsieh2",
"~Haisu_Zhou1",
"~Tianqing_Zou1",
"~Zerui_Cheng1",
"~Zhangyang_Wang1",
"~Pramod_Viswanath2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/527b4ef621918badbf88541f24daecd678a6888d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Planning",
"Game",
"Benchmark",
"Social Intelligence"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
yao2025spinbench,
title={{SPIN}-Bench: How Well Do {LLM}s Plan Strategically and Reason Socially?},
author={Jianzhu Yao and Kevin Wang and Ryan Hsieh and Haisu Zhou and Tianqing Zou and Zerui Cheng and Zhangyang Wang and Pramod Viswanath},
booktitle={Second Conference on Language Modeling},
year={2025},... | yao|spinbench_how_well_do_llms_plan_strategically_and_reason_socially | /attachment/b27f210e2adf29e68a923dd43e9fb24d62894bf2.zip | null | null | null | null | |
Improving Fisher Information Estimation and Efficiency for LoRA-based LLM Unlearning | We propose VILA, a scalable and efficient unlearning method for LLMs that addresses FILA's limitations by improving parameter importance estimation and reducing computational overhead. | LLMs have demonstrated remarkable performance across various tasks but face challenges related to unintentionally generating outputs containing sensitive information. A straightforward approach to address this issue is to retrain the model after excluding the problematic data. However, this approach incurs prohibitivel... | [
"Yejin Kim",
"Eunwon Kim",
"Buru Chang",
"Junsuk Choe"
] | https://openreview.net/forum?id=mTJW8Y1nd8 | mTJW8Y1nd8 | mTJW8Y1nd8 | [
"~Yejin_Kim7",
"~Eunwon_Kim1",
"~Buru_Chang1",
"~Junsuk_Choe1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8cc2caa1fac4c87a9c4e3277fd4b747ae7b3802f.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Machine Unlearning",
"Large Language Model"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
kim2025improving,
title={Improving Fisher Information Estimation and Efficiency for Lo{RA}-based {LLM} Unlearning},
author={Yejin Kim and Eunwon Kim and Buru Chang and Junsuk Choe},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=mTJW8Y1nd8}
} | kim|improving_fisher_information_estimation_and_efficiency_for_lorabased_llm_unlearning | null | null | null | null | null | |
ICQuant: Index Coding enables Low-bit LLM Quantization | This paper presents ICQuant, a novel framework that leverages outlier statistics to design an efficient index coding scheme for low-bit weight-only quantization. | The rapid deployment of Large Language Models (LLMs) highlights the need for efficient low-bit post-training quantization (PTQ) due to their high memory costs. A key challenge in weight quantization is the presence of outliers, which inflate quantization ranges and lead to large errors. While a number of outlier suppre... | [
"Xinlin Li",
"Osama Hanna",
"Christina Fragouli",
"Suhas Diggavi"
] | https://openreview.net/forum?id=m6nBgFSMTL | m6nBgFSMTL | m6nBgFSMTL | [
"~Xinlin_Li3",
"~Osama_Hanna1",
"~Christina_Fragouli1",
"~Suhas_Diggavi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ed1fe4cea396c575853e69ba69b116e193e547d6.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM Quantization",
"LLM Compression",
"Post Training Quantization"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
li2025icquant,
title={{ICQ}uant: Index Coding enables Low-bit {LLM} Quantization},
author={Xinlin Li and Osama Hanna and Christina Fragouli and Suhas Diggavi},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=m6nBgFSMTL}
} | li|icquant_index_coding_enables_lowbit_llm_quantization | null | null | null | null | null | |
LLM Unlearning Without an Expert Curated Dataset | Synthetic forget set to replace expert-curation for LLM unlearning. | Modern large language models often encode sensitive, harmful, or copyrighted knowledge, raising the need for post-hoc unlearning—the ability to remove specific domains of knowledge from a model without full retraining. A major bottleneck in current unlearning pipelines is constructing effective forget sets—datasets tha... | [
"Xiaoyuan Zhu",
"Muru Zhang",
"Ollie Liu",
"Robin Jia",
"Willie Neiswanger"
] | https://openreview.net/forum?id=m4F3kQCfGX | m4F3kQCfGX | m4F3kQCfGX | [
"~Xiaoyuan_Zhu2",
"~Muru_Zhang1",
"~Ollie_Liu1",
"~Robin_Jia1",
"~Willie_Neiswanger2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/0a5710cc0d3e8a268ba4e8727366abd1bd3e6b14.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"NLP",
"Machine Unlearning",
"Synthetic Data Generation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhu2025llm,
title={{LLM} Unlearning Without an Expert Curated Dataset},
author={Xiaoyuan Zhu and Muru Zhang and Ollie Liu and Robin Jia and Willie Neiswanger},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=m4F3kQCfGX}
} | zhu|llm_unlearning_without_an_expert_curated_dataset | null | null | null | null | null | |
How does Watermarking Affect Visual Language Models in Document Understanding? | Investigation of the robustness of VLM for document understanding task | Visual Language Models (VLMs) have become foundational models for document understanding tasks, widely used in the processing of complex multimodal documents across domains such as finance, law, and academia. However, documents often contain noise-like information, such as watermarks, which inevitably leads us to inqui... | [
"Chunxue Xu",
"Yiwei Wang",
"Bryan Hooi",
"Yujun Cai",
"Songze Li"
] | https://openreview.net/forum?id=lvQwn8eiRf | lvQwn8eiRf | lvQwn8eiRf | [
"~Chunxue_Xu1",
"~Yiwei_Wang2",
"~Bryan_Hooi1",
"~Yujun_Cai1",
"~Songze_Li1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/2d9289a5e67f0efe5aad593f326b2bedf28bf50f.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"VLMs",
"Document Understanding",
"Robustness"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
xu2025how,
title={How does Watermarking Affect Visual Language Models in Document Understanding?},
author={Chunxue Xu and Yiwei Wang and Bryan Hooi and Yujun Cai and Songze Li},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lvQwn8eiRf}
} | xu|how_does_watermarking_affect_visual_language_models_in_document_understanding | null | null | null | null | null | |
DynaSaur: Large Language Agents Beyond Predefined Actions | We propose a flexible LLM agent framework for open-ended environments, where it dynamically generates new actions when existing ones are insufficient. These actions accumulate over time for future reuse. | Existing LLM agent systems typically select actions from a fixed and predefined set at every step. While effective in closed, narrowly scoped environments, this approach presents two major challenges for real-world, open-ended scenarios: (1) it significantly restricts the planning and acting capabilities of LLM agents,... | [
"Dang Nguyen",
"Viet Dac Lai",
"Seunghyun Yoon",
"Ryan A. Rossi",
"Handong Zhao",
"Ruiyi Zhang",
"Puneet Mathur",
"Nedim Lipka",
"Yu Wang",
"Trung Bui",
"Franck Dernoncourt",
"Tianyi Zhou"
] | https://openreview.net/forum?id=lv0cJ2pWVd | lv0cJ2pWVd | lv0cJ2pWVd | [
"~Dang_Nguyen3",
"~Viet_Dac_Lai1",
"~Seunghyun_Yoon1",
"~Ryan_A._Rossi2",
"~Handong_Zhao3",
"~Ruiyi_Zhang3",
"~Puneet_Mathur2",
"~Nedim_Lipka1",
"~Yu_Wang41",
"~Trung_Bui1",
"~Franck_Dernoncourt1",
"~Tianyi_Zhou2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/9c0c2a1ca434928a59d8610c8e4f3cb8fe728cb9.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM",
"LLM agents"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
nguyen2025dynasaur,
title={DynaSaur: Large Language Agents Beyond Predefined Actions},
author={Dang Nguyen and Viet Dac Lai and Seunghyun Yoon and Ryan A. Rossi and Handong Zhao and Ruiyi Zhang and Puneet Mathur and Nedim Lipka and Yu Wang and Trung Bui and Franck Dernoncourt and Tianyi Zhou},
booktitle... | nguyen|dynasaur_large_language_agents_beyond_predefined_actions | null | null | null | null | null | |
Inducing Programmatic Skills for Agentic Tasks | We propose ASI, Agent Skill Induction, which induces and applies skill programs from web navigation experiences without supervision, yielding improved correctness and efficiency. | To succeed in common digital tasks such as web navigation, agents must carry out a variety of specialized tasks such as searching for products or planning a travel route. To tackle these tasks, agents can bootstrap themselves by learning task-specific skills online through interaction with the web environment. In this ... | [
"Zora Zhiruo Wang",
"Apurva Gandhi",
"Graham Neubig",
"Daniel Fried"
] | https://openreview.net/forum?id=lsAY6fWsog | lsAY6fWsog | lsAY6fWsog | [
"~Zora_Zhiruo_Wang1",
"~Apurva_Gandhi1",
"~Graham_Neubig1",
"~Daniel_Fried1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/367b824215ee6bfc801df80d296736d22b5ea8f8.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"agent",
"skill learning",
"web navigation",
"scalability",
"generalization"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wang2025inducing,
title={Inducing Programmatic Skills for Agentic Tasks},
author={Zora Zhiruo Wang and Apurva Gandhi and Graham Neubig and Daniel Fried},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lsAY6fWsog}
} | wang|inducing_programmatic_skills_for_agentic_tasks | /attachment/557818dcceefef95e993d00d56cf6bd03deaf89f.zip | null | null | null | null | |
C3PO: Critical-Layer, Core-Expert, Collaborative Pathway Optimization for Test-Time Expert Re-Mixing | Optimizing MoE LLM pathways at test-time via reference-based expert re-weighting, boosting accuracy by 7-15%. | Mixture-of-Experts (MoE) Large Language Models (LLMs) suffer from severely sub-optimal expert pathways—our study reveals that naive expert selection learned from pretraining leaves a surprising 10-20% accuracy gap for improvement. Motivated by this observation, we develop a novel class of test-time optimization methods... | [
"Zhongyang Li",
"Ziyue Li",
"Tianyi Zhou"
] | https://openreview.net/forum?id=lqC5J7pBP9 | lqC5J7pBP9 | lqC5J7pBP9 | [
"~Zhongyang_Li5",
"~Ziyue_Li1",
"~Tianyi_Zhou2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/27513ccd493f683c9f199ca9978819cb08488942.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Mixture-of-Experts",
"Large Language Models",
"Test-Time Learning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
li2025cpo,
title={C3{PO}: Critical-Layer, Core-Expert, Collaborative Pathway Optimization for Test-Time Expert Re-Mixing},
author={Zhongyang Li and Ziyue Li and Tianyi Zhou},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lqC5J7pBP9}
} | li|c3po_criticallayer_coreexpert_collaborative_pathway_optimization_for_testtime_expert_remixing | null | null | null | null | null | |
Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models | We propose rewriting low-quality web documents to improve their utility, thereby increasing the availability of pre-training data for language models | Scaling laws predict that the performance of large language models improves with increasing model size and data size. In practice, pre-training has been relying on massive web crawls, using almost all data sources publicly available on the internet so far. However, this pool of natural data does not grow at the same ra... | [
"Thao Nguyen",
"Yang Li",
"Olga Golovneva",
"Luke Zettlemoyer",
"Sewoong Oh",
"Ludwig Schmidt",
"Xian Li"
] | https://openreview.net/forum?id=lkjhBdz3rn | lkjhBdz3rn | lkjhBdz3rn | [
"~Thao_Nguyen3",
"~Yang_Li112",
"~Olga_Golovneva1",
"~Luke_Zettlemoyer1",
"~Sewoong_Oh3",
"~Ludwig_Schmidt1",
"~Xian_Li1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/467604cfb06de462129149a92b8208c1fb47d348.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"pretraining",
"synthetic data",
"rewriting",
"data curation for LLMs",
"data filtering"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
nguyen2025recycling,
title={Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models},
author={Thao Nguyen and Yang Li and Olga Golovneva and Luke Zettlemoyer and Sewoong Oh and Ludwig Schmidt and Xian Li},
booktitle={Second Conference on Language Modeling},
year... | nguyen|recycling_the_web_a_method_to_enhance_pretraining_data_quality_and_quantity_for_language_models | null | null | null | null | null | |
SuperBPE: Space Travel for Language Models | Superword tokenization leads to better and more efficient language models | The assumption across nearly all language model (LM) tokenization schemes is that tokens should be subwords, i.e., contained within word boundaries. While providing a seemingly reasonable inductive bias, is this common practice limiting the potential of modern LMs? Whitespace is not a reliable delimiter of meaning, as ... | [
"Alisa Liu",
"Jonathan Hayase",
"Valentin Hofmann",
"Sewoong Oh",
"Noah A. Smith",
"Yejin Choi"
] | https://openreview.net/forum?id=lcDRvffeNP | lcDRvffeNP | lcDRvffeNP | [
"~Alisa_Liu1",
"~Jonathan_Hayase2",
"~Valentin_Hofmann1",
"~Sewoong_Oh3",
"~Noah_A._Smith2",
"~Yejin_Choi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/f503ab922e85bb5ffab9a14ae81b12062a9064f7.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"tokenization",
"language modeling",
"efficiency"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
liu2025superbpe,
title={Super{BPE}: Space Travel for Language Models},
author={Alisa Liu and Jonathan Hayase and Valentin Hofmann and Sewoong Oh and Noah A. Smith and Yejin Choi},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lcDRvffeNP}
} | liu|superbpe_space_travel_for_language_models | null | null | null | null | null | |
A Survey on Personalized and Pluralistic Preference Alignment in Large Language Models | A survey on personalized and pluralistic preference Alignment in Large Language Models | Personalized preference alignment for large language models (LLMs), the process of tailoring LLMs to individual users' preferences, is an emerging research direction spanning the area of NLP and personalization. In this survey, we present an analysis of works on personalized alignment and modeling for LLMs. We introduc... | [
"Zhouhang Xie",
"Junda Wu",
"Yiran Shen",
"Raghav Jain",
"Yu Xia",
"Xintong Li",
"Aaron Chang",
"Ryan A. Rossi",
"Tong Yu",
"Sachin Kumar",
"Bodhisattwa Prasad Majumder",
"Jingbo Shang",
"Prithviraj Ammanabrolu",
"Julian McAuley"
] | https://openreview.net/forum?id=lSWOMjonL7 | lSWOMjonL7 | lSWOMjonL7 | [
"~Zhouhang_Xie1",
"~Junda_Wu1",
"~Yiran_Shen2",
"~Raghav_Jain1",
"~Yu_Xia9",
"~Xintong_Li2",
"~Aaron_Chang1",
"~Ryan_A._Rossi2",
"~Tong_Yu3",
"~Sachin_Kumar1",
"~Bodhisattwa_Prasad_Majumder1",
"~Jingbo_Shang2",
"~Prithviraj_Ammanabrolu1",
"~Julian_McAuley1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/2ce1323cfbae336695d501d9e61dbff93d15ea57.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Preference Alignment",
"Personalization",
"Pluralistic Alignment",
"Large Language Models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
xie2025a,
title={A Survey on Personalized and Pluralistic Preference Alignment in Large Language Models},
author={Zhouhang Xie and Junda Wu and Yiran Shen and Raghav Jain and Yu Xia and Xintong Li and Aaron Chang and Ryan A. Rossi and Tong Yu and Sachin Kumar and Bodhisattwa Prasad Majumder and Jingbo S... | xie|a_survey_on_personalized_and_pluralistic_preference_alignment_in_large_language_models | null | null | null | null | null | |
Task Vectors in In-Context Learning: Emergence, Formation, and Benefits | We study task vectors in transformers trained from scratch on synthetic tasks and find they emerge but remain indistinct. To enhance their formation, we introduce TVP-loss. Strong task vectors in deeper layers improve ICL on OOD prompts. | In-context learning is a remarkable capability of transformers, referring to their ability to adapt to specific tasks based on a short history or context. Previous research has found that task-specific information is locally encoded within models, though their emergence and functionality remain unclear due to opaque pr... | [
"Liu Yang",
"Ziqian Lin",
"Kangwook Lee",
"Dimitris Papailiopoulos",
"Robert D Nowak"
] | https://openreview.net/forum?id=lODGn1Rp5t | lODGn1Rp5t | lODGn1Rp5t | [
"~Liu_Yang6",
"~Ziqian_Lin1",
"~Kangwook_Lee1",
"~Dimitris_Papailiopoulos1",
"~Robert_D_Nowak1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/7e185d2734f706b41e72249356e60ec9fd37135e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"in-context learning; task vector"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
yang2025task,
title={Task Vectors in In-Context Learning: Emergence, Formation, and Benefits},
author={Liu Yang and Ziqian Lin and Kangwook Lee and Dimitris Papailiopoulos and Robert D Nowak},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lODGn1Rp5... | yang|task_vectors_in_incontext_learning_emergence_formation_and_benefits | null | null | null | null | null | |
SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models | We created a benchmark testing VLMs' ability to reason consistently across different modalities, revealing limitations in how models process semantically equivalent information based on format rather than meaning. | Evaluating whether vision–language models (VLMs) reason consistently across representations is challenging because modality comparisons are typically confounded by task differences and asymmetric information. We introduce SEAM, a benchmark that pairs semantically equivalent inputs across four domains that have existing... | [
"Zhenwei Tang",
"Difan Jiao",
"Blair Yang",
"Ashton Anderson"
] | https://openreview.net/forum?id=lI4LgGv4sX | lI4LgGv4sX | lI4LgGv4sX | [
"~Zhenwei_Tang1",
"~Difan_Jiao1",
"~Blair_Yang1",
"~Ashton_Anderson1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/980a13fe20145a2f7419388bb1bf725b023950e3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Vision-Language Models",
"Benchmark",
"Modality Imbalance"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
tang2025seam,
title={{SEAM}: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models},
author={Zhenwei Tang and Difan Jiao and Blair Yang and Ashton Anderson},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lI4LgGv4sX}
} | tang|seam_semantically_equivalent_across_modalities_benchmark_for_visionlanguage_models | null | null | null | null | null | |
Beyond the Reported Cutoff: Where Large Language Models Fall Short on Financial Knowledge | This paper evaluates Large Language Models' knowledge of historical financial data, finding they know more about larger, recent companies but are also prone to hallucinations about these firms. | Large Language Models (LLMs) are frequently utilized as sources of knowledge for question-answering. While it is known that LLMs may lack access to real-time data or newer data produced after the model's cutoff date, it is less clear how their knowledge spans across *historical* information. In this study, we assess th... | [
"Agam Shah",
"Liqin Ye",
"Sebastian Jaskowski",
"Wei Xu",
"Sudheer Chava"
] | https://openreview.net/forum?id=lEpPFmGH3L | lEpPFmGH3L | lEpPFmGH3L | [
"~Agam_Shah1",
"~Liqin_Ye1",
"~Sebastian_Jaskowski1",
"~Wei_Xu5",
"~Sudheer_Chava1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/b24fa9a8fd3c6721e3f957e197d5b44ec2782ba3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Knowledge Cutoff",
"Model Hallucinations"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
shah2025beyond,
title={Beyond the Reported Cutoff: Where Large Language Models Fall Short on Financial Knowledge},
author={Agam Shah and Liqin Ye and Sebastian Jaskowski and Wei Xu and Sudheer Chava},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=l... | shah|beyond_the_reported_cutoff_where_large_language_models_fall_short_on_financial_knowledge | null | null | null | null | null | |
Overcoming Vocabulary Constraints with Pixel-level Fallback | We augment pretrained language models with pixel-based text representations, overcoming vocabulary constraints, improving multilingual and cross-script performance | Subword tokenization requires balancing computational efficiency and vocabulary coverage, often leading to suboptimal performance on languages and scripts not prioritized during training.
We propose to augment pretrained language models with a vocabulary-free encoder that generates input embeddings from text rendered ... | [
"Jonas F. Lotz",
"Hendra Setiawan",
"Stephan Peitz",
"Yova Kementchedjhieva"
] | https://openreview.net/forum?id=lEaHNs2qEv | lEaHNs2qEv | lEaHNs2qEv | [
"~Jonas_F._Lotz1",
"~Hendra_Setiawan1",
"~Stephan_Peitz1",
"~Yova_Kementchedjhieva1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/bd9290fab67e049c39a67c9f2e6dde45900c894c.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"pixel-based text representations",
"machine translation",
"multilinguality",
"cross-lingual transfer",
"unseen scripts"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lotz2025overcoming,
title={Overcoming Vocabulary Constraints with Pixel-level Fallback},
author={Jonas F. Lotz and Hendra Setiawan and Stephan Peitz and Yova Kementchedjhieva},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=lEaHNs2qEv}
} | lotz|overcoming_vocabulary_constraints_with_pixellevel_fallback | null | null | null | null | null | |
EvidenceBench: A Benchmark for Extracting Evidence from Biomedical Papers | A large biomedical benchmark to evaluate LLMs' evidence-finding ability for scientific hypotheses and an automatic pipeline to create such benchmarks. | We study the task of automatically finding evidence relevant to hypotheses in biomedical papers. Finding relevant evidence is an important step when researchers investigate scientific hypotheses. We introduce EvidenceBench to measure models performance on this task, which is created by a novel pipeline that consists of... | [
"Jianyou Wang",
"Weili Cao",
"Kaicheng Wang",
"Xiaoyue Wang",
"Ashish Dalvi",
"Gino Prasad",
"Qishan Liang",
"Hsuan-lin Her",
"Mingwang",
"Qin Yang",
"Gene W. Yeo",
"David E Neal",
"Maxim Khan",
"Christopher D. Rosin",
"Ramamohan Paturi",
"Leon Bergen"
] | https://openreview.net/forum?id=lEQnUI5lEA | lEQnUI5lEA | lEQnUI5lEA | [
"~Jianyou_Wang1",
"~Weili_Cao1",
"~Kaicheng_Wang1",
"~Xiaoyue_Wang3",
"~Ashish_Dalvi1",
"~Gino_Prasad1",
"~Qishan_Liang1",
"~Hsuan-lin_Her1",
"~Mingwang1",
"~Qin_Yang5",
"~Gene_W._Yeo1",
"~David_E_Neal1",
"~Maxim_Khan1",
"~Christopher_D._Rosin1",
"~Ramamohan_Paturi1",
"~Leon_Bergen1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/b28cd425cb358879df700d6cdeb0bbdbc1a689df.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Biomedical Benchmark",
"Scientific Information Extraction",
"Large Language Models",
"BioNLP"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wang2025evidencebench,
title={EvidenceBench: A Benchmark for Extracting Evidence from Biomedical Papers},
author={Jianyou Wang and Weili Cao and Kaicheng Wang and Xiaoyue Wang and Ashish Dalvi and Gino Prasad and Qishan Liang and Hsuan-lin Her and Mingwang and Qin Yang and Gene W. Yeo and David E Neal a... | wang|evidencebench_a_benchmark_for_extracting_evidence_from_biomedical_papers | null | null | null | null | null | |
SEAL: Steerable Reasoning Calibration of Large Language Models for Free | We developed a training-free method that improves LLM accuracy and efficiency by calibrating CoT reasoning traces through a learned steering vector, reducing redundant thoughts and enhancing performance across multiple benchmarks. | Large Language Models (LLMs), such as OpenAI’s o1-series have demonstrated compelling capabilities for complex reasoning tasks via the extended chain-of-thought (CoT) reasoning mechanism. However, recent studies reveal substantial redundancy in the CoT reasoning traces, which not only increases inference latency but a... | [
"Runjin Chen",
"Zhenyu Zhang",
"Junyuan Hong",
"Souvik Kundu",
"Zhangyang Wang"
] | https://openreview.net/forum?id=klPszYDIRT | klPszYDIRT | klPszYDIRT | [
"~Runjin_Chen1",
"~Zhenyu_Zhang4",
"~Junyuan_Hong1",
"~Souvik_Kundu2",
"~Zhangyang_Wang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/78d6d04c381b639fc7c04ce750bff4724dec7a4f.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM",
"Reasoning",
"Representation Engineering"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
chen2025seal,
title={{SEAL}: Steerable Reasoning Calibration of Large Language Models for Free},
author={Runjin Chen and Zhenyu Zhang and Junyuan Hong and Souvik Kundu and Zhangyang Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=klPszYDIRT}
} | chen|seal_steerable_reasoning_calibration_of_large_language_models_for_free | null | null | null | null | null | |
ReasonIR: Training Retrievers for Reasoning Tasks | We present the first bi-encoder retriever specially trained to retrieve helpful documents for reasoning tasks. | We present ReasonIR-8B, the first retriever specifically trained for general reasoning tasks. Existing retrievers have shown limited gains on reasoning tasks, in part because existing training datasets focus on short factual queries tied to documents that straightforwardly answer them. We develop a synthetic data gener... | [
"Rulin Shao",
"Rui Qiao",
"Varsha Kishore",
"Niklas Muennighoff",
"Xi Victoria Lin",
"Daniela Rus",
"Bryan Kian Hsiang Low",
"Sewon Min",
"Wen-tau Yih",
"Pang Wei Koh",
"Luke Zettlemoyer"
] | https://openreview.net/forum?id=kkBCNLMbGj | kkBCNLMbGj | kkBCNLMbGj | [
"~Rulin_Shao1",
"~Rui_Qiao3",
"~Varsha_Kishore1",
"~Niklas_Muennighoff1",
"~Xi_Victoria_Lin1",
"~Daniela_Rus1",
"~Bryan_Kian_Hsiang_Low1",
"~Sewon_Min1",
"~Wen-tau_Yih1",
"~Pang_Wei_Koh1",
"~Luke_Zettlemoyer1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/08ca247ba1def28f58c2066c936038f437578e07.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"retriever",
"information retrieval",
"retrieval-augmented generation",
"reasoning",
"synthetic data"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
shao2025reasonir,
title={Reason{IR}: Training Retrievers for Reasoning Tasks},
author={Rulin Shao and Rui Qiao and Varsha Kishore and Niklas Muennighoff and Xi Victoria Lin and Daniela Rus and Bryan Kian Hsiang Low and Sewon Min and Wen-tau Yih and Pang Wei Koh and Luke Zettlemoyer},
booktitle={Second C... | shao|reasonir_training_retrievers_for_reasoning_tasks | null | null | null | null | null | |
How Multimodal LLMs Solve Image Tasks: A Lens on Visual Grounding, Task Reasoning, and Answer Decoding | We propose a probing framework to analyze how multimodal LLMs process visual and textual inputs across layers | Multimodal Large Language Models (MLLMs) have demonstrated strong performance across a wide range of vision-language tasks, yet their internal processing dynamics remain underexplored. In this work, we introduce a probing framework to systematically analyze how MLLMs process visual and textual inputs across layers. We ... | [
"Zhuoran Yu",
"Yong Jae Lee"
] | https://openreview.net/forum?id=kjNJYWvfPA | kjNJYWvfPA | kjNJYWvfPA | [
"~Zhuoran_Yu2",
"~Yong_Jae_Lee2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/f1fc281cc94ab858757534be1c0097d1b92201cc.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Multimodal LLM",
"Interpretability"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
yu2025how,
title={How Multimodal {LLM}s Solve Image Tasks: A Lens on Visual Grounding, Task Reasoning, and Answer Decoding},
author={Zhuoran Yu and Yong Jae Lee},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=kjNJYWvfPA}
} | yu|how_multimodal_llms_solve_image_tasks_a_lens_on_visual_grounding_task_reasoning_and_answer_decoding | null | null | null | null | null | |
SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs | We introduce Dynamic SAE Guardrails, a computationally efficient method that leverages sparse autoencoders for precision unlearning in LLMs, outperforming existing approaches while maintaining model utility. | Machine unlearning is a promising approach to improve LLM safety by removing unwanted knowledge from a trained model. However, prevailing gradient-based unlearning methods suffer from issues such as high computational costs, hyperparameter instability, poor sequential unlearning capability, vulnerability to relearning ... | [
"Aashiq Muhamed",
"Jacopo Bonato",
"Mona T. Diab",
"Virginia Smith"
] | https://openreview.net/forum?id=kaPAalWAp3 | kaPAalWAp3 | kaPAalWAp3 | [
"~Aashiq_Muhamed1",
"~Jacopo_Bonato1",
"~Mona_T._Diab1",
"~Virginia_Smith1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/15a48f1a716e9205e87c0e7e53e18753bc29238d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"unlearning",
"sparse autoencoders",
"representation editing",
"steering vectors",
"relearning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
muhamed2025saes,
title={{SAE}s Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in {LLM}s},
author={Aashiq Muhamed and Jacopo Bonato and Mona T. Diab and Virginia Smith},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/fo... | muhamed|saes_can_improve_unlearning_dynamic_sparse_autoencoder_guardrails_for_precision_unlearning_in_llms | null | null | null | null | null | |
Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers | We propose to improve inference-time scaling by jointly training a unified model for both reasoning and verification. | Prevalent reinforcement learning~(RL) methods for fine-tuning LLM reasoners, such as GRPO or Leave-one-out PPO, abandon the learned value function in favor of empirically estimated returns. This hinders test-time compute scaling that relies on using the value-function for verification.
In this work, we propose RL$^V$ ... | [
"Kusha Sareen",
"Morgane M Moss",
"Alessandro Sordoni",
"Arian Hosseini",
"Rishabh Agarwal"
] | https://openreview.net/forum?id=kVOrGZM5N7 | kVOrGZM5N7 | kVOrGZM5N7 | [
"~Kusha_Sareen1",
"~Morgane_M_Moss1",
"~Alessandro_Sordoni2",
"~Arian_Hosseini1",
"~Rishabh_Agarwal2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/3acf5484382857c965093513560345a4a8c7d01f.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM Reasoning",
"Verifiers",
"Test-time scaling",
"Reinforcement Learning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
sareen2025putting,
title={Putting the Value Back in {RL}: Better Test-Time Scaling by Unifying {LLM} Reasoners With Verifiers},
author={Kusha Sareen and Morgane M Moss and Alessandro Sordoni and Arian Hosseini and Rishabh Agarwal},
booktitle={Second Conference on Language Modeling},
year={2025},
url={ht... | sareen|putting_the_value_back_in_rl_better_testtime_scaling_by_unifying_llm_reasoners_with_verifiers | null | null | null | null | null | |
Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games | We evaluate the cooperative behavior of LLMs in a public goods game with norm enforcement and find that reasoning models are less effective at maintaining cooperation than traditional ones. | As large language models (LLMs) are increasingly deployed as autonomous agents, understanding their cooperation and social mechanisms is becoming increasingly important.
In particular, how LLMs balance self-interest and collective well-being is a critical challenge for ensuring alignment, robustness, and safe deploymen... | [
"David Guzman Piedrahita",
"Yongjin Yang",
"Mrinmaya Sachan",
"Giorgia Ramponi",
"Bernhard Schölkopf",
"Zhijing Jin"
] | https://openreview.net/forum?id=kH6LOHGjEl | kH6LOHGjEl | kH6LOHGjEl | [
"~David_Guzman_Piedrahita1",
"~Yongjin_Yang1",
"~Mrinmaya_Sachan3",
"~Giorgia_Ramponi1",
"~Bernhard_Schölkopf1",
"~Zhijing_Jin1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/a207da379702863ad85f59003fc2c5b4b7c47ac7.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Multi-Agent",
"Cooperation",
"Social Dilemmas",
"Public Goods Games",
"Institutional Choice",
"Costly Sanctioning",
"Norm Enforcement",
"Reasoning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
piedrahita2025corrupted,
title={Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games},
author={David Guzman Piedrahita and Yongjin Yang and Mrinmaya Sachan and Giorgia Ramponi and Bernhard Sch{\"o}lkopf and Zhijing Jin},
booktitle={Second Conference on Language Mode... | piedrahita|corrupted_by_reasoning_reasoning_language_models_become_freeriders_in_public_goods_games | /attachment/e77bf91abe796499b424be1e4bdb5bc6a3541fc2.zip | null | null | null | null | |
AdaptMI: Adaptive Skill-based In-context Math Instructions for Small Language Models | We introduce AdaptMI, an adaptive approach to selecting skill-based in-context math instructions for small language models. | In-context learning (ICL) allows a language model to improve its problem-solving capability when provided with suitable information in context. Since the choice of in-context information can be determined based on the problem itself, in-context learning is analogous to human learning from teachers in a classroom. Recen... | [
"Yinghui He",
"Abhishek Panigrahi",
"Yong Lin",
"Sanjeev Arora"
] | https://openreview.net/forum?id=k72RxnoS5g | k72RxnoS5g | k72RxnoS5g | [
"~Yinghui_He1",
"~Abhishek_Panigrahi1",
"~Yong_Lin2",
"~Sanjeev_Arora1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/4d231204c9988dda0204c56d1dcf4623ef1bd631.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Small language models",
"large language models",
"in-context learning",
"natural language processing"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
he2025adaptmi,
title={Adapt{MI}: Adaptive Skill-based In-context Math Instructions for Small Language Models},
author={Yinghui He and Abhishek Panigrahi and Yong Lin and Sanjeev Arora},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=k72RxnoS5g}
} | he|adaptmi_adaptive_skillbased_incontext_math_instructions_for_small_language_models | null | null | null | null | null | |
FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language | We introduce a new pre-training dataset curation pipeline based on FineWeb that we use to create a new large multilingual dataset, FineWeb2 | Pre-training state-of-the-art large language models (LLMs) requires vast amounts of clean and diverse text data. While the open development of large high-quality English pre-training datasets has seen substantial recent progress, training performant multilingual LLMs remains a challenge, in large part due to the inhere... | [
"Guilherme Penedo",
"Hynek Kydlíček",
"Vinko Sabolčec",
"Bettina Messmer",
"Negar Foroutan",
"Amir Hossein Kargaran",
"Colin Raffel",
"Martin Jaggi",
"Leandro Von Werra",
"Thomas Wolf"
] | https://openreview.net/forum?id=jnRBe6zatP | jnRBe6zatP | jnRBe6zatP | [
"~Guilherme_Penedo1",
"~Hynek_Kydlíček1",
"~Vinko_Sabolčec1",
"~Bettina_Messmer1",
"~Negar_Foroutan1",
"~Amir_Hossein_Kargaran1",
"~Colin_Raffel1",
"~Martin_Jaggi1",
"~Leandro_Von_Werra1",
"~Thomas_Wolf1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8a8d8d04776824b23e7bd4683c04c4f4104f6682.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"multilingual",
"dataset",
"pretraining",
"web data",
"llm"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | true | While there might not be a direct risk but since there are model released on large quantity of web-crawled data, it would be useful to include a potential risk statement at the end of the paper.
| @inproceedings{
penedo2025fineweb,
title={FineWeb2: One Pipeline to Scale Them All {\textemdash} Adapting Pre-Training Data Processing to Every Language},
author={Guilherme Penedo and Hynek Kydl{\'\i}{\v{c}}ek and Vinko Sabol{\v{c}}ec and Bettina Messmer and Negar Foroutan and Amir Hossein Kargaran and Colin Raffel and... | penedo|fineweb2_one_pipeline_to_scale_them_all_adapting_pretraining_data_processing_to_every_language | null | true | null | null | null | |
AI-Slop to AI-Polish? Aligning Language Models through Edit-Based Writing Rewards and Test-time computation | AI models struggle to assess writing quality, but the new Writing Quality Benchmark and specialized reward model enable significant improvements to AI-generated text. | AI-generated text is proliferating across domains, from creative writing and journalism to marketing content and scientific articles. Models can follow user-provided instructions to generate coherent and grammatically correct outputs but in this work, we study a more fundamental question: how do we evaluate and improve... | [
"Tuhin Chakrabarty",
"Philippe Laban",
"Chien-Sheng Wu"
] | https://openreview.net/forum?id=jeDYcjuZIV | jeDYcjuZIV | jeDYcjuZIV | [
"~Tuhin_Chakrabarty2",
"~Philippe_Laban1",
"~Chien-Sheng_Wu1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/9c9ec96e904859c276d16b3667db86b735894ec3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM",
"Writing",
"Reward Models",
"Alignment",
"Human Centered NLP",
"Test Time Compute",
"Text Editing",
"Behavioral Science"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
chakrabarty2025aislop,
title={{AI}-Slop to {AI}-Polish? Aligning Language Models through Edit-Based Writing Rewards and Test-time computation},
author={Tuhin Chakrabarty and Philippe Laban and Chien-Sheng Wu},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/f... | chakrabarty|aislop_to_aipolish_aligning_language_models_through_editbased_writing_rewards_and_testtime_computation | null | null | null | null | null | |
EuroBERT: Scaling Multilingual Encoders for European Languages | We introduce EuroBERT, a family of multilingual encoders leveraging recent architectural advances, achieving state-of-the-art performance across diverse tasks with support for sequences up to 8,192 tokens. | General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirectional encoder models. Despite their wide applicability, encoders have been recently overshadowed by advances in generative decoder-only models. However, many innovations driving... | [
"Nicolas Boizard",
"Hippolyte Gisserot-Boukhlef",
"Duarte Miguel Alves",
"Andre Martins",
"Ayoub Hammal",
"Caio Corro",
"CELINE HUDELOT",
"Emmanuel Malherbe",
"Etienne Malaboeuf",
"Fanny Jourdan",
"Gabriel Hautreux",
"João Alves",
"Kevin El Haddad",
"Manuel Faysse",
"Maxime Peyrard",
"... | https://openreview.net/forum?id=jdOC24msVq | jdOC24msVq | jdOC24msVq | [
"~Nicolas_Boizard1",
"~Hippolyte_Gisserot-Boukhlef1",
"~Duarte_Miguel_Alves1",
"~Andre_Martins1",
"~Ayoub_Hammal1",
"~Caio_Corro2",
"~CELINE_HUDELOT1",
"~Emmanuel_Malherbe3",
"~Etienne_Malaboeuf1",
"~Fanny_Jourdan1",
"~Gabriel_Hautreux2",
"~João_Alves2",
"~Kevin_El_Haddad1",
"~Manuel_Fayss... | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5b43e38fbf30639e53eb283215e3f86c4dfa0b8c.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Encoder",
"Multilingual",
"EuroBERT",
"Training",
"Vector Representations",
"Bidirectional",
"European"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
boizard2025eurobert,
title={Euro{BERT}: Scaling Multilingual Encoders for European Languages},
author={Nicolas Boizard and Hippolyte Gisserot-Boukhlef and Duarte Miguel Alves and Andre Martins and Ayoub Hammal and Caio Corro and CELINE HUDELOT and Emmanuel Malherbe and Etienne Malaboeuf and Fanny Jourda... | boizard|eurobert_scaling_multilingual_encoders_for_european_languages | null | null | null | null | null | |
MALT: Improving Reasoning with Multi-Agent LLM Training | We introduce a multi-agent post-training approach to improve the reasoning and self-correction performance of a generator, verifier, and refinement model working together | Large Language Models (LLMs) often produce answers with a single chain-of-thought, which restricts their ability to explore reasoning paths or self-correct flawed outputs in complex tasks. In this paper, we introduce MALT (Multi-Agent LLM Training), a novel post-training strategy that divides the reasoning process into... | [
"Sumeet Ramesh Motwani",
"Chandler Smith",
"Rocktim Jyoti Das",
"Rafael Rafailov",
"Philip Torr",
"Ivan Laptev",
"Fabio Pizzati",
"Ronald Clark",
"Christian Schroeder de Witt"
] | https://openreview.net/forum?id=jXP9bgFack | jXP9bgFack | jXP9bgFack | [
"~Sumeet_Ramesh_Motwani1",
"~Chandler_Smith1",
"~Rocktim_Jyoti_Das2",
"~Rafael_Rafailov1",
"~Philip_Torr1",
"~Ivan_Laptev1",
"~Fabio_Pizzati1",
"~Ronald_Clark2",
"~Christian_Schroeder_de_Witt1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/da3f367150d10b65b2dcaa8152a1aea745c9a7bd.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"reasoning",
"multi-agent systems",
"post-training",
"reinforcement learning",
"large language models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
motwani2025malt,
title={{MALT}: Improving Reasoning with Multi-Agent {LLM} Training},
author={Sumeet Ramesh Motwani and Chandler Smith and Rocktim Jyoti Das and Rafael Rafailov and Philip Torr and Ivan Laptev and Fabio Pizzati and Ronald Clark and Christian Schroeder de Witt},
booktitle={Second Conferen... | motwani|malt_improving_reasoning_with_multiagent_llm_training | /attachment/c362d320dbebaac8a22e3ce459c2bf0981b28842.zip | null | null | null | null | |
Can Test-Time Scaling Improve World Foundation Model? | Test time scaling could work for world foundation models and shows a clear scaling law. Smaller model with test time scaling is even better than x2 larger pretrained model. A extensible tookit will be opensourced for evaluating performance of WFM. | World foundation models, which simulate the physical world by predicting future states from current observations and inputs, have become central to many applications in physical intelligence, including autonomous driving and robotics. However, these models require substantial computational resources for pretraining and... | [
"Wenyan Cong",
"Hanqing Zhu",
"Peihao Wang",
"Bangya Liu",
"Dejia Xu",
"Kevin Wang",
"David Z. Pan",
"Yan Wang",
"Zhiwen Fan",
"Zhangyang Wang"
] | https://openreview.net/forum?id=jSmpq7IRYe | jSmpq7IRYe | jSmpq7IRYe | [
"~Wenyan_Cong1",
"~Hanqing_Zhu1",
"~Peihao_Wang1",
"~Bangya_Liu1",
"~Dejia_Xu1",
"~Kevin_Wang4",
"~David_Z._Pan1",
"~Yan_Wang10",
"~Zhiwen_Fan2",
"~Zhangyang_Wang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/fb37c34624a030a952ca49f34e233a4b8989d236.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"world foundation model",
"test time scaling",
"autoregressive video generation",
"evaluation tookit"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
cong2025can,
title={Can Test-Time Scaling Improve World Foundation Model?},
author={Wenyan Cong and Hanqing Zhu and Peihao Wang and Bangya Liu and Dejia Xu and Kevin Wang and David Z. Pan and Yan Wang and Zhiwen Fan and Zhangyang Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
ur... | cong|can_testtime_scaling_improve_world_foundation_model | null | null | null | null | null | |
Implicit In-Context Learning: Evidence from Artificial Language Experiments | LLMs show human-like implicit learning during inference, but different models excel in different linguistic domains, pointing to distinct in-context learning mechanisms influenced by model architecture. | Humans acquire language through implicit learning, absorbing complex patterns without explicit awareness. While large language models (LLMs) demonstrate impressive linguistic capabilities, it remains unclear whether they exhibit human-like pattern recognition during in-context learning at inferencing level. We adapted ... | [
"Xiaomeng Ma",
"Qihui Xu"
] | https://openreview.net/forum?id=jST2VzWUFb | jST2VzWUFb | jST2VzWUFb | [
"~Xiaomeng_Ma1",
"~Qihui_Xu1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ee53e57c5115c95f27c7d0afcfe22b6389effb30.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"implicit learning",
"artificial language learning",
"in-context learning",
"psycholinguistics",
"cognitive science"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | true | Only a minor thing. The paper uses probably copyrighted images from other papers in Figure 1 and 3. They should produce new figures with the original numbers as they did in Figure 2.
| @inproceedings{
ma2025implicit,
title={Implicit In-Context Learning: Evidence from Artificial Language Experiments},
author={Xiaomeng Ma and Qihui Xu},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=jST2VzWUFb}
} | ma|implicit_incontext_learning_evidence_from_artificial_language_experiments | null | null | null | null | null | |
Post-training for Efficient Communication via Convention Formation | We introduce a post-training method and new tasks to test and improve LLMs' abilities in forming conventions for efficient communication. | Humans communicate with increasing efficiency in multi-turn interactions, by adapting their language and forming ad-hoc conventions. In contrast, prior work shows that LLMs do not naturally show this behavior. We develop a post-training process to develop this ability through targeted fine-tuning on heuristically ident... | [
"Yilun Hua",
"Evan Wang",
"Yoav Artzi"
] | https://openreview.net/forum?id=jRGGmbhX2s | jRGGmbhX2s | jRGGmbhX2s | [
"~Yilun_Hua1",
"~Evan_Wang2",
"~Yoav_Artzi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/90eee569c161e32eb84ea65de4a8205e9fa60de2.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Interaction",
"Communication Efficiency",
"Linguistic Convention",
"Post-training",
"Alignment",
"LLM",
"In-context learning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
hua2025posttraining,
title={Post-training for Efficient Communication via Convention Formation},
author={Yilun Hua and Evan Wang and Yoav Artzi},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=jRGGmbhX2s}
} | hua|posttraining_for_efficient_communication_via_convention_formation | null | null | null | null | null | |
Tulu 3: Pushing Frontiers in Open Language Model Post-Training | A new multi-stage post-training recipe scaling preference learning and reinforcement learning with verifiable rewards. | Language model post-training is applied to refine behaviors and unlock
new skills across a wide range of language models, but open recipes for
applying these techniques lag behind proprietary ones. The underlying
training data and recipes for post-training are simultaneously the most im-
portant pieces of the puzzle an... | [
"Nathan Lambert",
"Jacob Morrison",
"Valentina Pyatkin",
"Shengyi Huang",
"Hamish Ivison",
"Faeze Brahman",
"Lester James Validad Miranda",
"Alisa Liu",
"Nouha Dziri",
"Xinxi Lyu",
"Yuling Gu",
"Saumya Malik",
"Victoria Graf",
"Jena D. Hwang",
"Jiangjiang Yang",
"Ronan Le Bras",
"Oyv... | https://openreview.net/forum?id=i1uGbfHHpH | i1uGbfHHpH | i1uGbfHHpH | [
"~Nathan_Lambert1",
"~Jacob_Morrison2",
"~Valentina_Pyatkin1",
"~Shengyi_Huang1",
"~Hamish_Ivison1",
"~Faeze_Brahman1",
"~Lester_James_Validad_Miranda1",
"~Alisa_Liu1",
"~Nouha_Dziri2",
"~Xinxi_Lyu1",
"~Yuling_Gu1",
"~Saumya_Malik1",
"~Victoria_Graf1",
"~Jena_D._Hwang1",
"~Jiangjiang_Yan... | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/9c0d921fcc7c90227f3e1bcba16bfea6f63ad480.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"post-training",
"reinforcement learning",
"preference learning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lambert2025tulu,
title={Tulu 3: Pushing Frontiers in Open Language Model Post-Training},
author={Nathan Lambert and Jacob Morrison and Valentina Pyatkin and Shengyi Huang and Hamish Ivison and Faeze Brahman and Lester James Validad Miranda and Alisa Liu and Nouha Dziri and Xinxi Lyu and Yuling Gu and Sa... | lambert|tulu_3_pushing_frontiers_in_open_language_model_posttraining | null | true | null | null | null | |
Beyond Blanket Masking: Examining Granularity for Privacy Protection in Images Captured by Blind and Low Vision Users | We propose a fine-grained privacy protection framework that selectively masks only high-risk private information while preserving low-risk information in images taken by blind and low vision users for improved usability. | As visual assistant systems powered by visual language models (VLMs) become more prevalent, concerns over user privacy have grown, particularly for blind and low vision users who may unknowingly capture personal private information in their images. Existing privacy protection methods rely on coarse-grained segmentation... | [
"Jeffri Murrugarra-Llerena",
"Haoran Niu",
"K. Suzanne Barber",
"Hal Daumé III",
"Yang Trista Cao",
"Paola Cascante-Bonilla"
] | https://openreview.net/forum?id=hLjoekkPiJ | hLjoekkPiJ | hLjoekkPiJ | [
"~Jeffri_Murrugarra-Llerena1",
"~Haoran_Niu1",
"~K._Suzanne_Barber1",
"~Hal_Daumé_III1",
"~Yang_Trista_Cao1",
"~Paola_Cascante-Bonilla1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c24fbd6345ba739cef3f37e046cb5b2524fc8652.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"visual language models",
"privacy",
"safety",
"accessibility"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
murrugarra-llerena2025beyond,
title={Beyond Blanket Masking: Examining Granularity for Privacy Protection in Images Captured by Blind and Low Vision Users},
author={Jeffri Murrugarra-Llerena and Haoran Niu and K. Suzanne Barber and Hal Daum{\'e} III and Yang Trista Cao and Paola Cascante-Bonilla},
bookt... | murrugarrallerena|beyond_blanket_masking_examining_granularity_for_privacy_protection_in_images_captured_by_blind_and_low_vision_users | null | null | null | null | null | |
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning | This paper proposes a new RL framework to pursue the performance limit that can be achieved through outcome reward-based reinforcement learning for mathematical reasoning tasks, where only binary outcome rewards are easily accessible. | Reasoning abilities, especially those for solving complex math problems, are crucial components of general intelligence. Recent advances by proprietary companies, such as o-series models of OpenAI, have made remarkable progress on reasoning tasks. However, the complete technical details remain unrevealed, and the techn... | [
"Chengqi Lyu",
"Songyang Gao",
"Yuzhe Gu",
"Wenwei Zhang",
"Jianfei Gao",
"Kuikun Liu",
"Ziyi Wang",
"Shuaibin Li",
"Qian Zhao",
"Haian Huang",
"Weihan Cao",
"Jiangning Liu",
"Hongwei Liu",
"Junnan Liu",
"Songyang Zhang",
"Dahua Lin",
"Kai Chen"
] | https://openreview.net/forum?id=hLg2rzBJR2 | hLg2rzBJR2 | hLg2rzBJR2 | [
"~Chengqi_Lyu1",
"~Songyang_Gao1",
"~Yuzhe_Gu1",
"~Wenwei_Zhang1",
"~Jianfei_Gao1",
"~Kuikun_Liu1",
"~Ziyi_Wang30",
"~Shuaibin_Li2",
"~Qian_Zhao10",
"~Haian_Huang1",
"~Weihan_Cao1",
"~Jiangning_Liu1",
"~Hongwei_Liu2",
"~Junnan_Liu1",
"~Songyang_Zhang1",
"~Dahua_Lin1",
"~Kai_Chen4"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5d9ab08857ddd9047f14e3abbcb0430b6b09ada9.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Model",
"Reinforcement Learning",
"Mathmatical Reasoning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lyu2025exploring,
title={Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning},
author={Chengqi Lyu and Songyang Gao and Yuzhe Gu and Wenwei Zhang and Jianfei Gao and Kuikun Liu and Ziyi Wang and Shuaibin Li and Qian Zhao and Haian Huang and Weihan Cao and Jiangning Liu and Hongwei ... | lyu|exploring_the_limit_of_outcome_reward_for_learning_mathematical_reasoning | null | null | null | null | null | |
The World According to LLMs: How Geographic Origin Influences LLMs' Entity Deduction Capabilities | LLMs demonstrate geographic bias in entity deduction games, with notably better performance on entities from the Global North and West despite controlling for language, popularity and frequency factors. | Large Language Models (LLMs) have been extensively tuned to mitigate explicit biases, yet they often exhibit subtle implicit biases rooted in their pre-training data. Rather than directly probing LLMs with human-crafted questions that may trigger guardrails, we propose studying how models behave when they proactively a... | [
"Harsh Nishant Lalai",
"Raj Sanjay Shah",
"Jiaxin Pei",
"Sashank Varma",
"Yi-Chia Wang",
"Ali Emami"
] | https://openreview.net/forum?id=hJtvCfDfs1 | hJtvCfDfs1 | hJtvCfDfs1 | [
"~Harsh_Nishant_Lalai1",
"~Raj_Sanjay_Shah2",
"~Jiaxin_Pei1",
"~Sashank_Varma1",
"~Yi-Chia_Wang2",
"~Ali_Emami3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ac4433d186627b5e757785570169152bc828290f.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"geographic representation",
"LLM evaluation",
"fairness and bias",
"reasoning capabilities",
"cross-cultural NLP",
"interactive question answering"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lalai2025the,
title={The World According to {LLM}s: How Geographic Origin Influences {LLM}s' Entity Deduction Capabilities},
author={Harsh Nishant Lalai and Raj Sanjay Shah and Jiaxin Pei and Sashank Varma and Yi-Chia Wang and Ali Emami},
booktitle={Second Conference on Language Modeling},
year={2025},
... | lalai|the_world_according_to_llms_how_geographic_origin_influences_llms_entity_deduction_capabilities | /attachment/074af523bf6b035bfdf44772c9856eb01071c044.zip | null | null | null | null | |
FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios | We introduce FacTool, a tool augmented factuality detection framework that can effectively detect diverse factual errors generated by LLMs. | The emergence of generative pre-trained models has facilitated the synthesis of high-quality text but has also posed challenges in identifying factual errors in the generated text. In particular: (1) A wider range of tasks now face an increasing risk of containing factual errors when handled by generative models. (2) T... | [
"Ethan Chern",
"Steffi Chern",
"Shiqi Chen",
"Weizhe Yuan",
"Kehua Feng",
"Chunting Zhou",
"Junxian He",
"Graham Neubig",
"Pengfei Liu"
] | https://openreview.net/forum?id=hJkQL9VtWT | hJkQL9VtWT | hJkQL9VtWT | [
"~Ethan_Chern1",
"~Steffi_Chern1",
"~Shiqi_Chen3",
"~Weizhe_Yuan1",
"~Kehua_Feng1",
"~Chunting_Zhou1",
"~Junxian_He1",
"~Graham_Neubig1",
"~Pengfei_Liu1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/56beb802a5975ad23bc08b1f979c1bbbfdf9b831.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"factuality",
"llm",
"hallucination"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
chern2025factool,
title={FacTool: Factuality Detection in Generative {AI} -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios},
author={Ethan Chern and Steffi Chern and Shiqi Chen and Weizhe Yuan and Kehua Feng and Chunting Zhou and Junxian He and Graham Neubig and Pengfei Liu},
book... | chern|factool_factuality_detection_in_generative_ai_a_tool_augmented_framework_for_multitask_and_multidomain_scenarios | null | null | null | null | null | |
Overflow Prevention Enhances Long-Context Recurrent LLMs | We identify that recurrent LLMs suffer from recurrent memory overflows that limit their performance in long-context tasks. We propose OPRM, a training-free overflow-prevention mechanism that achieves significant gains in many long-context tasks. | A recent trend in LLMs is developing recurrent sub-quadratic models that improve long-context processing efficiency. We investigate leading large long-context models, focusing on how their fixed-size recurrent memory affects their performance. Our experiments reveal that, even when these models are trained for extended... | [
"Assaf Ben-Kish",
"Itamar Zimerman",
"Muhammad Jehanzeb Mirza",
"Lior Wolf",
"James R. Glass",
"Leonid Karlinsky",
"Raja Giryes"
] | https://openreview.net/forum?id=h99hJlU99U | h99hJlU99U | h99hJlU99U | [
"~Assaf_Ben-Kish1",
"~Itamar_Zimerman1",
"~Muhammad_Jehanzeb_Mirza1",
"~Lior_Wolf1",
"~James_R._Glass1",
"~Leonid_Karlinsky3",
"~Raja_Giryes1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/efdf046a9a269338d76057e9cbd738e378ebcfd4.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Mamba",
"Sub-Quadratic Models",
"Long Context",
"Long-Range Language Modeling",
"RNNs"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
ben-kish2025overflow,
title={Overflow Prevention Enhances Long-Context Recurrent {LLM}s},
author={Assaf Ben-Kish and Itamar Zimerman and Muhammad Jehanzeb Mirza and Lior Wolf and James R. Glass and Leonid Karlinsky and Raja Giryes},
booktitle={Second Conference on Language Modeling},
year={2025},
url={h... | benkish|overflow_prevention_enhances_longcontext_recurrent_llms | /attachment/d052d7d6c9526dfe93dd56e2282dfe73efb8d2a8.zip | null | null | null | null | |
Both Direct and Indirect Evidence Contribute to Dative Alternation Preferences in Language Models | Through manipulating word-order preferences in datives and non-datives in the training sets of language models, we find that they acquire dative alternation preferences from both direct and indirect evidence. | Language models (LMs) tend to show human-like preferences on a number of syntactic phenomena, but the extent to which these are attributable to direct exposure to the phenomena or more general properties of language is unclear. We explore this with the English dative alternation (DO: "gave Y the X" vs. PO: "gave the X ... | [
"Qing Yao",
"Kanishka Misra",
"Leonie Weissweiler",
"Kyle Mahowald"
] | https://openreview.net/forum?id=h5SRsDax8v | h5SRsDax8v | h5SRsDax8v | [
"~Qing_Yao1",
"~Kanishka_Misra1",
"~Leonie_Weissweiler1",
"~Kyle_Mahowald1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8e4eb5c7ff5e692e1ee71bfed0fc2db5ec51f2cc.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"linguistics",
"dative alternation",
"indirect evidence",
"language learning",
"cognitive science",
"linguistic constructions"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
yao2025both,
title={Both Direct and Indirect Evidence Contribute to Dative Alternation Preferences in Language Models},
author={Qing Yao and Kanishka Misra and Leonie Weissweiler and Kyle Mahowald},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=h5S... | yao|both_direct_and_indirect_evidence_contribute_to_dative_alternation_preferences_in_language_models | /attachment/95f95f9867e13b8b85bd505fc06b68fc5343fa85.zip | null | null | null | null | |
Training Plug-and-Play Knowledge Modules with Deep Context Distillation | We encapsulate knowledge from a document inside a LoRA adapter via distillation | Dynamically integrating new or rapidly evolving information after (Large) Language Model pre-training remains challenging, particularly in low-data scenarios or when dealing with private and specialized documents. In-context learning and retrieval-augmented generation (RAG) face limitations, including their high infere... | [
"Lucas Caccia",
"Alan Ansell",
"Edoardo Ponti",
"Ivan Vulić",
"Alessandro Sordoni"
] | https://openreview.net/forum?id=ghyyHZYORi | ghyyHZYORi | ghyyHZYORi | [
"~Lucas_Caccia1",
"~Alan_Ansell1",
"~Edoardo_Ponti1",
"~Ivan_Vulić1",
"~Alessandro_Sordoni2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e6440e102c61ff2e77b350b613c2c70b72b3c8cc.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"knowledge extraction",
"document understanding",
"modular learning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
caccia2025training,
title={Training Plug-and-Play Knowledge Modules with Deep Context Distillation},
author={Lucas Caccia and Alan Ansell and Edoardo Ponti and Ivan Vuli{\'c} and Alessandro Sordoni},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=gh... | caccia|training_plugandplay_knowledge_modules_with_deep_context_distillation | null | null | null | null | null | |
StagFormer: Time Staggering Decoder only Transformers | We propose a novel variant of the Transformer architecture for decoder only language modeling where we break the causal flow of information along the layers of a model by staggering in the time axis. | Standard decoding in a Transformer based language model is inherently sequential as we wait for a token’s embedding to pass through all the layers in the network before starting the generation of the next token. In this work, we propose anew architecture StagFormer (Staggered Transformer), which staggered execution alo... | [
"Dylan J Cutler",
"Arun Kandoor",
"Nishanth Dikkala",
"Nikunj Saunshi",
"Xin Wang",
"Rina Panigrahy"
] | https://openreview.net/forum?id=gOKTe1KI8K | gOKTe1KI8K | gOKTe1KI8K | [
"~Dylan_J_Cutler1",
"~Arun_Kandoor1",
"~Nishanth_Dikkala1",
"~Nikunj_Saunshi1",
"~Xin_Wang30",
"~Rina_Panigrahy1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ba36b6a43243381888f9fe458c1dd690d8466235.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"staggered execution",
"decoder only language models",
"efficiency",
"novel architectures",
"generative models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
cutler2025stagformer,
title={StagFormer: Time Staggering Decoder only Transformers},
author={Dylan J Cutler and Arun Kandoor and Nishanth Dikkala and Nikunj Saunshi and Xin Wang and Rina Panigrahy},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=gOK... | cutler|stagformer_time_staggering_decoder_only_transformers | null | null | null | null | null | |
X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents | X-Teaming, a scalable multi-agent framework that achieves state-of-the-art multi-turn jailbreaking of language models while X-Guard trains models to defend against these attacks. | Multi-turn interactions with language models (LMs) pose critical safety risks, as harmful intent can be strategically spread across exchanges. Yet, the vast majority of prior work has focused on single-turn safety, while adaptability and diversity remain among the key challenges of multi-turn red-teaming. To address th... | [
"Salman Rahman",
"Liwei Jiang",
"James Shiffer",
"Genglin Liu",
"Sheriff Issaka",
"Md Rizwan Parvez",
"Hamid Palangi",
"Kai-Wei Chang",
"Yejin Choi",
"Saadia Gabriel"
] | https://openreview.net/forum?id=gKfj7Jb1kj | gKfj7Jb1kj | gKfj7Jb1kj | [
"~Salman_Rahman1",
"~Liwei_Jiang2",
"~James_Shiffer1",
"~Genglin_Liu1",
"~Sheriff_Issaka1",
"~Md_Rizwan_Parvez1",
"~Hamid_Palangi1",
"~Kai-Wei_Chang1",
"~Yejin_Choi1",
"~Saadia_Gabriel1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/3e4a1c4d08cce66b395c76b84a9a11c7dcae8c65.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Multi-turn Jailbreaks",
"Adaptive Multi-Agent",
"Conversational AI Safety",
"Red-Teaming",
"Defensive Alignment"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
rahman2025xteaming,
title={X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents},
author={Salman Rahman and Liwei Jiang and James Shiffer and Genglin Liu and Sheriff Issaka and Md Rizwan Parvez and Hamid Palangi and Kai-Wei Chang and Yejin Choi and Saadia Gabriel},
booktitle={Second ... | rahman|xteaming_multiturn_jailbreaks_and_defenses_with_adaptive_multiagents | null | null | null | null | null | |
SQuat: Subspace-orthogonal KV Cache Quantization | We propose a KV cache quantization method that preserves task-critical information throughout the quantization process. | The key-value (KV) cache accelerates LLMs decoding by storing KV tensors from previously generated tokens. It reduces redundant computation at the cost of increased memory usage. To mitigate this overhead, existing approaches compress KV tensors into lower-bit representations; however, quantization errors can accumulat... | [
"Hao Wang",
"Ligong Han",
"Kai Xu",
"Akash Srivastava"
] | https://openreview.net/forum?id=gKdhzBiHay | gKdhzBiHay | gKdhzBiHay | [
"~Hao_Wang22",
"~Ligong_Han1",
"~Kai_Xu4",
"~Akash_Srivastava1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ed8d739e7f3da1993f38d6c9bb76c233b8435be1.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"KV cache quantization",
"LLMs"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wang2025squat,
title={{SQ}uat: Subspace-orthogonal {KV} Cache Quantization},
author={Hao Wang and Ligong Han and Kai Xu and Akash Srivastava},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=gKdhzBiHay}
} | wang|squat_subspaceorthogonal_kv_cache_quantization | null | null | null | null | null | |
KVSink: Understanding and Enhancing the Preservation of Attention Sinks in KV Cache Quantization for LLMs | Understanding and Enhancing the Preservation of Attention Sinks in KV Cache Quantization for LLMs | Key-Value (KV) cache quantization has become a widely adopted optimization technique for efficient large language models (LLMs) inference by reducing KV cache memory usage and mitigating memory-bound constraints.
Recent studies have emphasized the importance of preserving the original precision of KVs for the first few... | [
"Zunhai Su",
"Kehong Yuan"
] | https://openreview.net/forum?id=gIqb6zWZoO | gIqb6zWZoO | gIqb6zWZoO | [
"~Zunhai_Su1",
"~Kehong_Yuan1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/b192f1bfa40f51a5501e78eb839aa697e1a1a6c3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"quantization",
"kv cache",
"transformer",
"llm",
"attention"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
su2025kvsink,
title={{KVS}ink: Understanding and Enhancing the Preservation of Attention Sinks in {KV} Cache Quantization for {LLM}s},
author={Zunhai Su and Kehong Yuan},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=gIqb6zWZoO}
} | su|kvsink_understanding_and_enhancing_the_preservation_of_attention_sinks_in_kv_cache_quantization_for_llms | null | true | null | null | null | |
Efficient Construction of Model Family through Progressive Training Using Model Expansion | We propose a progressive training approach that efficiently builds a family of LLMs, reducing total computational requirements while achieving comparable or even better performance. | As Large Language Models (LLMs) gain widespread practical applica-
tion, offering model families with varying parameter sizes has become
standard practice to accommodate diverse computational requirements.
Traditionally, each model in the family is trained independently, incurring
computational costs that scale additiv... | [
"Kazuki Yano",
"Sho Takase",
"Sosuke Kobayashi",
"Shun Kiyono",
"Jun Suzuki"
] | https://openreview.net/forum?id=fuBrcTH8NM | fuBrcTH8NM | fuBrcTH8NM | [
"~Kazuki_Yano1",
"~Sho_Takase2",
"~Sosuke_Kobayashi1",
"~Shun_Kiyono1",
"~Jun_Suzuki1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5558b4586a726c29e22f45704837021d08ddb3bf.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"pre-training",
"model familly",
"compute efficiency"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
yano2025efficient,
title={Efficient Construction of Model Family through Progressive Training Using Model Expansion},
author={Kazuki Yano and Sho Takase and Sosuke Kobayashi and Shun Kiyono and Jun Suzuki},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/foru... | yano|efficient_construction_of_model_family_through_progressive_training_using_model_expansion | null | null | null | null | null | |
UNVEILING: What Makes Linguistics Olympiad Puzzles Tricky for LLMs? | The study presents a linguistic features-based annotation of Linguistics Olympiad puzzles to find LLM weaknesses; LLMs are bad at puzzles with higher morphological complexity, dissimilar to English, and when the puzzle is data constrained. | Large language models (LLMs) have demonstrated potential in reasoning tasks, but their performance on linguistics puzzles remains consistently poor. These puzzles, often derived from Linguistics Olympiad (LO) contests, provide a minimal contamination environment to assess LLMs' linguistic reasoning abilities across low... | [
"Mukund Choudhary",
"KV Aditya Srivatsa",
"Gaurja Aeron",
"Antara Raaghavi Bhattacharya",
"Dang Khoa Dang Dinh",
"Ikhlasul Akmal Hanif",
"Daria Kotova",
"Ekaterina Kochmar",
"Monojit Choudhury"
] | https://openreview.net/forum?id=fcRcl1EXc4 | fcRcl1EXc4 | fcRcl1EXc4 | [
"~Mukund_Choudhary1",
"~KV_Aditya_Srivatsa1",
"~Gaurja_Aeron1",
"~Antara_Raaghavi_Bhattacharya1",
"~Dang_Khoa_Dang_Dinh1",
"~Ikhlasul_Akmal_Hanif1",
"~Daria_Kotova1",
"~Ekaterina_Kochmar2",
"~Monojit_Choudhury1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e2a9b0fcf4a176a28b878dd7d16d5725a0164c0c.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"linguistic reasoning",
"metalinguistics",
"LLM evaluation",
"morphology",
"linguistics olympiad",
"interpretability",
"low resource languages",
"annotation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
choudhary2025unveiling,
title={{UNVEILING}: What Makes Linguistics Olympiad Puzzles Tricky for {LLM}s?},
author={Mukund Choudhary and KV Aditya Srivatsa and Gaurja Aeron and Antara Raaghavi Bhattacharya and Dang Khoa Dang Dinh and Ikhlasul Akmal Hanif and Daria Kotova and Ekaterina Kochmar and Monojit C... | choudhary|unveiling_what_makes_linguistics_olympiad_puzzles_tricky_for_llms | null | null | null | null | null | |
AgentRewardBench: Evaluating Automatic Evaluations of Web Agent Trajectories | AgentRewardBench is a benchmark that evaluates how well Large Language Model (LLM) judges align with human preferences when assessing autonomous web agents, using over 1,200 expert-reviewed trajectories across five benchmarks | Web agents enable users to perform tasks on web browsers through natural language interaction. Evaluating web agents trajectories is an important problem, since it helps us determine whether the agent successfully completed the tasks. Rule-based methods are widely used for this purpose, but they are challenging to exte... | [
"Xing Han Lù",
"Amirhossein Kazemnejad",
"Nicholas Meade",
"Arkil Patel",
"Dongchan Shin",
"Alejandra Zambrano",
"Karolina Stanczak",
"Peter Shaw",
"Christopher Pal",
"Siva Reddy"
] | https://openreview.net/forum?id=fQcUZMPIvu | fQcUZMPIvu | fQcUZMPIvu | [
"~Xing_Han_Lù1",
"~Amirhossein_Kazemnejad1",
"~Nicholas_Meade1",
"~Arkil_Patel1",
"~Dongchan_Shin1",
"~Alejandra_Zambrano1",
"~Karolina_Stanczak1",
"~Peter_Shaw1",
"~Christopher_Pal1",
"~Siva_Reddy1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/9049329e5673f53bcd91fc9e3157946c0407caff.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Agent",
"Web Agent",
"LLM Judge",
"LLM-as-a-Judge",
"Digital Agent",
"Benchmark",
"Reward Modeling"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lu2025agentrewardbench,
title={AgentRewardBench: Evaluating Automatic Evaluations of Web Agent Trajectories},
author={Xing Han L{\`u} and Amirhossein Kazemnejad and Nicholas Meade and Arkil Patel and Dongchan Shin and Alejandra Zambrano and Karolina Stanczak and Peter Shaw and Christopher Pal and Siva R... | lù|agentrewardbench_evaluating_automatic_evaluations_of_web_agent_trajectories | null | null | null | null | null | |
Inside-Out: Hidden Factual Knowledge in LLMs | We introduce a framework for evaluating the gap between the knowledge LLMs encode internally and what they express in their outputs, and provide strong evidence of this gap across popular LLMs. | This work presents a framework for assessing whether large language models (LLMs) encode more factual knowledge in their parameters than what they express in their outputs. While a few studies hint at this possibility, none has clearly defined or demonstrated this phenomenon. We first propose a formal definition of kno... | [
"Zorik Gekhman",
"Eyal Ben-David",
"Hadas Orgad",
"Eran Ofek",
"Yonatan Belinkov",
"Idan Szpektor",
"Jonathan Herzig",
"Roi Reichart"
] | https://openreview.net/forum?id=f7GG1MbsSM | f7GG1MbsSM | f7GG1MbsSM | [
"~Zorik_Gekhman1",
"~Eyal_Ben-David1",
"~Hadas_Orgad1",
"~Eran_Ofek1",
"~Yonatan_Belinkov1",
"~Idan_Szpektor1",
"~Jonathan_Herzig2",
"~Roi_Reichart1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/13c1300909f9eb3d5e428b69bc513b2e0ea8d642.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLMs",
"Knowledge"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
gekhman2025insideout,
title={Inside-Out: Hidden Factual Knowledge in {LLM}s},
author={Zorik Gekhman and Eyal Ben-David and Hadas Orgad and Eran Ofek and Yonatan Belinkov and Idan Szpektor and Jonathan Herzig and Roi Reichart},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https:/... | gekhman|insideout_hidden_factual_knowledge_in_llms | null | null | null | null | null | |
The Unlearning Mirage: A Dynamic Framework for Evaluating LLM Unlearning | A Dynamic Framework for Evaluating LLM Unlearning | Unlearning in Large Language Models (LLMs) aims to enhance safety, mitigate biases, and comply with legal mandates, such as the right to be forgotten. However, existing unlearning methods are brittle: minor query modifications, such as multi-hop reasoning and entity aliasing, can recover supposedly forgotten informatio... | [
"Raj Sanjay Shah",
"Jing Huang",
"Keerthiram Murugesan",
"Nathalie Baracaldo",
"Diyi Yang"
] | https://openreview.net/forum?id=exW2SFJK4H | exW2SFJK4H | exW2SFJK4H | [
"~Raj_Sanjay_Shah2",
"~Jing_Huang2",
"~Keerthiram_Murugesan1",
"~Nathalie_Baracaldo1",
"~Diyi_Yang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c17d1f36ddb6d284517474f548310cba9ce3ae00.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Unlearning evaluation",
"Multi-hop reasoning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
shah2025the,
title={The Unlearning Mirage: A Dynamic Framework for Evaluating {LLM} Unlearning},
author={Raj Sanjay Shah and Jing Huang and Keerthiram Murugesan and Nathalie Baracaldo and Diyi Yang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=ex... | shah|the_unlearning_mirage_a_dynamic_framework_for_evaluating_llm_unlearning | /attachment/3effe50b2de608ddbd7719e8b65eb2fd13f7c786.zip | true | null | null | null | |
EvalAgents: Discovering Implicit Evaluation Criteria from the Web | We propose a novel framework EvalAgent that dynamically generates grounded, implicit evaluation criteria for a given prompt based on retrieved expert advice. | Evaluation of language model outputs on structured writing tasks is typically conducted with a number of desirable criteria presented to human evaluators or large language models (LLMs). For instance, on a prompt like "Help me draft an academic talk on coffee intake vs research productivity", a model response may be ev... | [
"Manya Wadhwa",
"Zayne Rea Sprague",
"Chaitanya Malaviya",
"Philippe Laban",
"Junyi Jessy Li",
"Greg Durrett"
] | https://openreview.net/forum?id=erGpkHCybv | erGpkHCybv | erGpkHCybv | [
"~Manya_Wadhwa1",
"~Zayne_Rea_Sprague1",
"~Chaitanya_Malaviya1",
"~Philippe_Laban1",
"~Junyi_Jessy_Li2",
"~Greg_Durrett1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/231c145f57a04150de2e76cfc963745238701095.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"evaluation",
"writing",
"large language models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wadhwa2025evalagents,
title={EvalAgents: Discovering Implicit Evaluation Criteria from the Web},
author={Manya Wadhwa and Zayne Rea Sprague and Chaitanya Malaviya and Philippe Laban and Junyi Jessy Li and Greg Durrett},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openre... | wadhwa|evalagents_discovering_implicit_evaluation_criteria_from_the_web | null | null | null | null | null | |
Discovering Knowledge Deficiencies of Language Models on Massive Knowledge Base | We propose stochastic error ascend, an optimization-based framework that efficiently identifies and refines failure modes in LLMs, discovering significantly more errors than existing methods while reducing evaluation costs. | Large language models (LLMs) possess impressive linguistic capabilities but often fail to faithfully retain factual knowledge, leading to hallucinations and unreliable outputs. Understanding LLMs' knowledge deficiencies by exhaustively evaluating against full-scale knowledge bases is computationally prohibitive, especi... | [
"Linxin Song",
"Xuwei Ding",
"Jieyu Zhang",
"Taiwei Shi",
"Ryotaro Shimizu",
"Rahul Gupta",
"Yang Liu",
"Jian Kang",
"Jieyu Zhao"
] | https://openreview.net/forum?id=eqNItk1sWo | eqNItk1sWo | eqNItk1sWo | [
"~Linxin_Song1",
"~Xuwei_Ding1",
"~Jieyu_Zhang1",
"~Taiwei_Shi1",
"~Ryotaro_Shimizu1",
"~Rahul_Gupta3",
"~Yang_Liu60",
"~Jian_Kang1",
"~Jieyu_Zhao1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/084e39ff598ebc6cfeb04aecfccaafaf4bf56c00.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Evaluation",
"Misinformation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
song2025discovering,
title={Discovering Knowledge Deficiencies of Language Models on Massive Knowledge Base},
author={Linxin Song and Xuwei Ding and Jieyu Zhang and Taiwei Shi and Ryotaro Shimizu and Rahul Gupta and Yang Liu and Jian Kang and Jieyu Zhao},
booktitle={Second Conference on Language Modelin... | song|discovering_knowledge_deficiencies_of_language_models_on_massive_knowledge_base | null | null | null | null | null | |
MuSeD: A Multimodal Spanish Dataset for Sexism Detection in Social Media Videos | We present MuSeD, a multimodal Spanish dataset for sexism detection in videos, with an innovative annotation framework for analyzing the contribution of textual and multimodal labels. We evaluate the performance of LLMs and multimodal LLMs on MuSeD. | Sexism is generally defined as prejudice and discrimination based on sex or gender, affecting every sector of society, from social institutions to relationships and individual behavior. Social media platforms amplify the impact of sexism by conveying discriminatory content not only through text but also across multiple... | [
"Laura De Grazia",
"Pol Pastells",
"Mauro Vázquez Chas",
"Desmond Elliott",
"Danae Sanchez Villegas",
"Mireia Farrús",
"Mariona Taulé Delor"
] | https://openreview.net/forum?id=eSAv7GKVFt | eSAv7GKVFt | eSAv7GKVFt | [
"~Laura_De_Grazia1",
"~Pol_Pastells1",
"~Mauro_Vázquez_Chas1",
"~Desmond_Elliott1",
"~Danae_Sanchez_Villegas1",
"~Mireia_Farrús1",
"~Mariona_Taulé_Delor1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/19195e99dd51cc5a9d15e559e82f4506a2d30845.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"sexism",
"multimodal",
"classification",
"social media",
"LLMs"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | true | Dataset contains samples with discrimination/stereotype/inequality/objectification in videos, especially sensitive samples from BitChute platform where annotators returned ~94% samples as sexist.
The proposed Spanish dataset for sexism detection may contribute to the emergence of sexual harassment-related public opini... | @inproceedings{
grazia2025mused,
title={MuSeD: A Multimodal Spanish Dataset for Sexism Detection in Social Media Videos},
author={Laura De Grazia and Pol Pastells and Mauro V{\'a}zquez Chas and Desmond Elliott and Danae Sanchez Villegas and Mireia Farr{\'u}s and Mariona Taul{\'e} Delor},
booktitle={Second Conference on... | grazia|mused_a_multimodal_spanish_dataset_for_sexism_detection_in_social_media_videos | null | null | null | null | null | |
Meta-Learning for Speeding Up Large Model Inference in Decentralized Environments | We propose a meta-learning framework to optimize inference acceleration in decentralized AI systems based on task-specific data, promoting more cost-effective and scalable AI deployment. | The deployment of large-scale models, such as large language models (LLMs), incurs substantial costs due to their computational demands. To mitigate these costs and address challenges related to scalability and data security, there is a growing shift towards decentralized systems for model deployment, where choosing ef... | [
"Yipeng Du",
"Zihao Wang",
"Ahmad Farhan",
"Claudio Angione",
"Harry Yang",
"Fielding Johnston",
"James P. Buban",
"Yue Zhao",
"Yuzhe Yang"
] | https://openreview.net/forum?id=eLWn2XVMHA | eLWn2XVMHA | eLWn2XVMHA | [
"~Yipeng_Du2",
"~Zihao_Wang36",
"~Ahmad_Farhan1",
"~Claudio_Angione1",
"~Harry_Yang2",
"~Fielding_Johnston1",
"~James_P._Buban1",
"~Yue_Zhao13",
"~Yuzhe_Yang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/2448403da60ff435885d137ba6343485b7151611.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Fast inference",
"LLMs",
"meta learning",
"decentralized systems"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
du2025metalearning,
title={Meta-Learning for Speeding Up Large Model Inference in Decentralized Environments},
author={Yipeng Du and Zihao Wang and Ahmad Farhan and Claudio Angione and Harry Yang and Fielding Johnston and James P. Buban and Yue Zhao and Yuzhe Yang},
booktitle={Second Conference on Langu... | du|metalearning_for_speeding_up_large_model_inference_in_decentralized_environments | null | null | null | null | null | |
(Im)possibility of Automated Hallucination Detection in Large Language Models | We propose a novel theoretical model for hallucination detection and show that it is generally impossible to automate this task only with positive examples; however, if we have negative examples, the task becomes much easier. | Is automated hallucination detection fundamentally possible?
In this paper, we introduce a theoretical framework to rigorously study the (im)possibility of automatically detecting hallucinations produced by large language models (LLMs). Our model builds on the classical Gold-Angluin framework of language identification... | [
"Amin Karbasi",
"Omar Montasser",
"John Sous",
"Grigoris Velegkas"
] | https://openreview.net/forum?id=e5jWdZIX0Q | e5jWdZIX0Q | e5jWdZIX0Q | [
"~Amin_Karbasi3",
"~Omar_Montasser1",
"~John_Sous1",
"~Grigoris_Velegkas1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/6b7c25bf886c16a2b1e8e9a0fb45dfbf9edae089.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"hallucinations",
"theory",
"RLHF"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
karbasi2025impossibility,
title={(Im)possibility of Automated Hallucination Detection in Large Language Models},
author={Amin Karbasi and Omar Montasser and John Sous and Grigoris Velegkas},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=e5jWdZIX0Q}... | karbasi|impossibility_of_automated_hallucination_detection_in_large_language_models | null | null | null | null | null | |
Overfill: Two-Stage Models for Efficient Language Model Decoding | Leveraging more compute during prefill, OverFill improves generation quality with minimal latency overhead. | Large language models (LLMs) excel across diverse tasks but face significant deployment challenges due to high inference costs. LLM inference comprises prefill (compute-bound) and decode (memory-bound) stages, with decode dominating latency particularly for long sequences. Current decoder-only models handle both stages... | [
"Woojeong Kim",
"Junxiong Wang",
"Jing Nathan Yan",
"Mohamed S. Abdelfattah",
"Alexander M Rush"
] | https://openreview.net/forum?id=e112iu5ssg | e112iu5ssg | e112iu5ssg | [
"~Woojeong_Kim1",
"~Junxiong_Wang1",
"~Jing_Nathan_Yan1",
"~Mohamed_S._Abdelfattah1",
"~Alexander_M_Rush1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/a53da3fa4a7edb32a0e94623f81ffc790ebd31f8.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"deep learning",
"large language models",
"inference efficiency"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
kim2025overfill,
title={Overfill: Two-Stage Models for Efficient Language Model Decoding},
author={Woojeong Kim and Junxiong Wang and Jing Nathan Yan and Mohamed S. Abdelfattah and Alexander M Rush},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=e1... | kim|overfill_twostage_models_for_efficient_language_model_decoding | null | null | null | null | null | |
URANIA: Differentially Private Insights into AI Use | We introduce a novel framework primarily designed for generating insights about LLM chatbot interactions while providing differential privacy guarantees, while also being applicable to other text corpora. | We introduce _Urania_, a novel framework for generating insights about LLM chatbot interactions with rigorous differential privacy (DP) guarantees. The framework employs a private clustering mechanism and innovative keyword extraction methods, including frequency-based, TF-IDF-based, and LLM-guided approaches. By lever... | [
"Daogao Liu",
"Edith Cohen",
"Badih Ghazi",
"Peter Kairouz",
"Pritish Kamath",
"Alexander Knop",
"Ravi Kumar",
"Pasin Manurangsi",
"Adam Sealfon",
"Da Yu",
"Chiyuan Zhang"
] | https://openreview.net/forum?id=dujG4nGClA | dujG4nGClA | dujG4nGClA | [
"~Daogao_Liu1",
"~Edith_Cohen1",
"~Badih_Ghazi1",
"~Peter_Kairouz1",
"~Pritish_Kamath2",
"~Alexander_Knop1",
"~Ravi_Kumar1",
"~Pasin_Manurangsi2",
"~Adam_Sealfon1",
"~Da_Yu1",
"~Chiyuan_Zhang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ed4ba9cf9757208ce5d3327f79b31d0c9f1d18b9.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Differential Privacy",
"Clustering",
"Summarization"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
liu2025urania,
title={{URANIA}: Differentially Private Insights into {AI} Use},
author={Daogao Liu and Edith Cohen and Badih Ghazi and Peter Kairouz and Pritish Kamath and Alexander Knop and Ravi Kumar and Pasin Manurangsi and Adam Sealfon and Da Yu and Chiyuan Zhang},
booktitle={Second Conference on La... | liu|urania_differentially_private_insights_into_ai_use | null | null | null | null | null | |
PersonaEval: Are LLM Evaluators Human Enough to Judge Role-Play? | We introduce PersonaEval, a benchmark showing that LLMs struggle to judge role-play like humans. Even top models fail basic role identification, highlighting a need for more human-like reasoning in LLM evaluators. | Current role-play studies often rely on unvalidated LLM-as-a-judge paradigms, which may fail to reflect how humans perceive role fidelity. A key prerequisite for human-aligned evaluation is role identification, the ability to recognize who is speaking based on dialogue context. We argue that any meaningful judgment of ... | [
"Lingfeng Zhou",
"Jialing Zhang",
"Jin Gao",
"Mohan Jiang",
"Dequan Wang"
] | https://openreview.net/forum?id=drdrFhKYjP | drdrFhKYjP | drdrFhKYjP | [
"~Lingfeng_Zhou1",
"~Jialing_Zhang1",
"~Jin_Gao3",
"~Mohan_Jiang1",
"~Dequan_Wang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/7d82995478de95962a51816e94a3e690c84e9d2e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Role-play",
"evaluating LLM evaluators",
"benchmark"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhou2025personaeval,
title={PersonaEval: Are {LLM} Evaluators Human Enough to Judge Role-Play?},
author={Lingfeng Zhou and Jialing Zhang and Jin Gao and Mohan Jiang and Dequan Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=drdrFhKYjP}
} | zhou|personaeval_are_llm_evaluators_human_enough_to_judge_roleplay | /attachment/6a25cb35829c49d55a1670963857bef598b95c9e.zip | null | null | null | null | |
Learning to Reason for Long-Form Story Generation | We propose a long-form story generation task, Next-Chapter Prediction, and a novel reward formulation that allows us to learn reasoning traces which improve predicted chapters without a labeled dataset. | Generating high-quality stories spanning thousands of tokens requires competency across a variety of skills, from tracking plot and character arcs to keeping a consistent and engaging style. Due to the difficulty of sourcing labeled datasets and precise quality measurements, most work using large language models (LLMs)... | [
"Alexander Gurung",
"Mirella Lapata"
] | https://openreview.net/forum?id=dr3eg5ehR2 | dr3eg5ehR2 | dr3eg5ehR2 | [
"~Alexander_Gurung1",
"~Mirella_Lapata1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/bfa23a57d4114b772b5398b348d3308aa0ebfd0f.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"story generation",
"reasoning",
"reinforcement learning",
"long-context generation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
gurung2025learning,
title={Learning to Reason for Long-Form Story Generation},
author={Alexander Gurung and Mirella Lapata},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=dr3eg5ehR2}
} | gurung|learning_to_reason_for_longform_story_generation | null | null | null | null | null | |
Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining | We conduct a systematic end-to-end study of RL fine-tuning from scratch for mathematical reasoning, uncovering how RL shapes model behavior across scales and data mixtures. | Reinforcement learning (RL)-based fine-tuning has become a crucial step in post-training language models for advanced mathematical reasoning and coding. Following the success of frontier reasoning models, recent work has demonstrated that RL fine-tuning consistently improves performance, even in smaller-scale models; h... | [
"Rosie Zhao",
"Alexandru Meterez",
"Sham M. Kakade",
"Cengiz Pehlevan",
"Samy Jelassi",
"Eran Malach"
] | https://openreview.net/forum?id=dp4KWuSDzj | dp4KWuSDzj | dp4KWuSDzj | [
"~Rosie_Zhao1",
"~Alexandru_Meterez1",
"~Sham_M._Kakade1",
"~Cengiz_Pehlevan2",
"~Samy_Jelassi1",
"~Eran_Malach3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8cfad45ef47f433c49770fdee1de3c3007efecc7.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"reinforcement learning",
"language models",
"post-training",
"ppo",
"pretraining",
"reasoning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhao2025echo,
title={Echo Chamber: {RL} Post-training Amplifies Behaviors Learned in Pretraining},
author={Rosie Zhao and Alexandru Meterez and Sham M. Kakade and Cengiz Pehlevan and Samy Jelassi and Eran Malach},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.n... | zhao|echo_chamber_rl_posttraining_amplifies_behaviors_learned_in_pretraining | null | null | null | null | null | |
Evaluating LLMs on Chinese Idiom Translation | We evaluate large language models on Chinese idiom translation across multiple domains and introduce new metrics that reliably measures idiom translation quality, significantly outperforming existing translation metrics. | Idioms, whose figurative meanings usually differ from their literal interpretations, are common in everyday language, especially in Chinese, where they often contain historical references and follow specific structural patterns. Despite recent progress in machine translation with large language models, little is known ... | [
"Cai Yang",
"Yao Dou",
"David Heineman",
"Xiaofeng Wu",
"Wei Xu"
] | https://openreview.net/forum?id=dkE5rveDuh | dkE5rveDuh | dkE5rveDuh | [
"~Cai_Yang1",
"~Yao_Dou1",
"~David_Heineman1",
"~Xiaofeng_Wu5",
"~Wei_Xu5"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/288488f3af0e0caf3be74ad0d0cefb3b2efbb459.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Model Evaluation",
"Chinese Idioms",
"Meta Analysis",
"Multilingual Evaluation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
yang2025evaluating,
title={Evaluating {LLM}s on Chinese Idiom Translation},
author={Cai Yang and Yao Dou and David Heineman and Xiaofeng Wu and Wei Xu},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=dkE5rveDuh}
} | yang|evaluating_llms_on_chinese_idiom_translation | null | null | This submission is NOT exempt from the Reciprocal Reviewing requirement. (We expect most submissions to fall in this category.) | ~Yao_Dou1 | {
"readers": [
"colmweb.org/COLM/2025/Conference",
"colmweb.org/COLM/2025/Conference/Submission992/Authors"
]
} | |
QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization | Fine-grained Evaluation of Content Selection for Text Summarization | How to properly conduct human evaluations for text summarization is a longstanding challenge. The Pyramid human evaluation protocol, which assesses content selection by breaking the reference summary into sub-units and verifying their presence in the system summary, has been widely adopted. However, it suffers from a l... | [
"Shiyue Zhang",
"David Wan",
"Arie Cattan",
"Ayal Klein",
"Ido Dagan",
"Mohit Bansal"
] | https://openreview.net/forum?id=dZRzInscvA | dZRzInscvA | dZRzInscvA | [
"~Shiyue_Zhang1",
"~David_Wan1",
"~Arie_Cattan1",
"~Ayal_Klein1",
"~Ido_Dagan1",
"~Mohit_Bansal2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/4120b6c3ef2897eadd231d9b69c23815f5944c22.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Evaluation",
"Summarization"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhang2025qapyramid,
title={{QAP}yramid: Fine-grained Evaluation of Content Selection for Text Summarization},
author={Shiyue Zhang and David Wan and Arie Cattan and Ayal Klein and Ido Dagan and Mohit Bansal},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/fo... | zhang|qapyramid_finegrained_evaluation_of_content_selection_for_text_summarization | null | null | null | null | null | |
Steering the CensorShip: Uncovering Representation Vectors for LLM "Thought'' Control | We examine safety-tuned LLMs and discover representation vectors for measuring and controlling censorship imposed through refusal and thought suppression. | Large language models (LLMs) have transformed the way we access information. These models are often tuned to refuse to comply with requests that are considered harmful and to produce responses that better align with the preferences of those who control the models. To understand how this "censorship'" works. We use repr... | [
"Hannah Cyberey",
"David Evans"
] | https://openreview.net/forum?id=dVqZBagXF3 | dVqZBagXF3 | dVqZBagXF3 | [
"~Hannah_Cyberey1",
"~David_Evans1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/70893e89e94379603250043cfb412820efbd25a4.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"censorship",
"activation steering",
"representation engineering",
"reasoning LLMs"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
cyberey2025steering,
title={Steering the CensorShip: Uncovering Representation Vectors for {LLM} ''Thought'' Control},
author={Hannah Cyberey and David Evans},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=dVqZBagXF3}
} | cyberey|steering_the_censorship_uncovering_representation_vectors_for_llm_thought_control | null | null | null | null | null | |
Cutting the Root of Hallucination: Structural Trimming for Vulnerability Mitigation in Code LLMs | LLMs hallucinate code often with security risks. We trace these structurally, prune them surgically, and predict repair effectiveness. Our method patches code and mitigates risk using a transferable score (CSHS). | We introduce a structural perspective on hallucinations in code-generating language models, framing them as causality anchors in syntax graphs that trigger cascading semantic errors and latent security flaws. This work is the first to systematically connect code hallucinations with vulnerability risks, offering a unifi... | [
"Yage Zhang"
] | https://openreview.net/forum?id=dU4Y2sNfJ2 | dU4Y2sNfJ2 | dU4Y2sNfJ2 | [
"~Yage_Zhang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/94228dff9c0d4e67d4c92dc5132ee037a4340a14.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM hallucinations",
"code generation",
"program repair",
"vulnerability mitigation",
"structural pruning",
"abstract syntax tree",
"hallucination detection",
"CSHS",
"model-agnostic risk estimation",
"generative code safety"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhang2025cutting,
title={Cutting the Root of Hallucination: Structural Trimming for Vulnerability Mitigation in Code {LLM}s},
author={Yage Zhang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=dU4Y2sNfJ2}
} | zhang|cutting_the_root_of_hallucination_structural_trimming_for_vulnerability_mitigation_in_code_llms | null | null | null | null | null | |
Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning | We propose an approach that integrates LLM-based evolutionary search with RL fine-tuning for accelerated discovery of algorithms, as demonstrated on combinatorial optimization tasks. | Discovering efficient algorithms for solving complex problems has been an outstanding challenge in mathematics and computer science, requiring substantial human expertise over the years. Recent advancements in evolutionary search with large language models (LLMs) have shown promise in accelerating the discovery of algo... | [
"Anja Šurina",
"Amin Mansouri",
"Lars C.P.M. Quaedvlieg",
"Amal Seddas",
"Maryna Viazovska",
"Emmanuel Abbe",
"Caglar Gulcehre"
] | https://openreview.net/forum?id=dNW3RGW0gi | dNW3RGW0gi | dNW3RGW0gi | [
"~Anja_Šurina1",
"~Amin_Mansouri1",
"~Lars_C.P.M._Quaedvlieg1",
"~Amal_Seddas1",
"~Maryna_Viazovska1",
"~Emmanuel_Abbe1",
"~Caglar_Gulcehre1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/92babb3133c8776c7888a177c504da576de4c7f4.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Reinforcement Learning",
"Evolutionary Search",
"Algorithm Discovery",
"Self-Improvement",
"AI for Math"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
surina2025algorithm,
title={Algorithm Discovery With {LLM}s: Evolutionary Search Meets Reinforcement Learning},
author={Anja {\v{S}}urina and Amin Mansouri and Lars C.P.M. Quaedvlieg and Amal Seddas and Maryna Viazovska and Emmanuel Abbe and Caglar Gulcehre},
booktitle={Second Conference on Language Mod... | urina|algorithm_discovery_with_llms_evolutionary_search_meets_reinforcement_learning | null | null | null | null | null | |
You Cannot Feed Two Birds with One Score: the Accuracy-Naturalness Tradeoff in Translation | We prove mathematically and demonstrate empirically that optimizing a single metric for machine translation *cannot* lead to a system that is both accurate and fluent. We also establish a connection between no-reference metrics and our theory. | The goal of translation, be it by human or by machine, is, given some text in a source language, to produce text in a target language that simultaneously 1) preserves the meaning of the source text and 2) achieves natural expression in the target language. However, researchers in the machine translation community usual... | [
"Gergely Flamich",
"David Vilar",
"Jan-Thorsten Peter",
"Markus Freitag"
] | https://openreview.net/forum?id=d9EkgbZZH9 | d9EkgbZZH9 | d9EkgbZZH9 | [
"~Gergely_Flamich1",
"~David_Vilar1",
"~Jan-Thorsten_Peter1",
"~Markus_Freitag2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e125a1f2f817db9daf4c4a2ed3b825ae306572f5.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"translation",
"accuracy",
"naturalness",
"tradeoff",
"distortion",
"perception",
"no-reference metric"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
flamich2025you,
title={You Cannot Feed Two Birds with One Score: the Accuracy-Naturalness Tradeoff in Translation},
author={Gergely Flamich and David Vilar and Jan-Thorsten Peter and Markus Freitag},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=d9... | flamich|you_cannot_feed_two_birds_with_one_score_the_accuracynaturalness_tradeoff_in_translation | null | null | null | null | null | |
Teach Old SAEs New Domain Tricks with Boosting | We propose a method to add domain-specific features into a pre-trained SAE. | Sparse Autoencoders have emerged as powerful tools for interpreting the internal representations of Large Language Models, yet they often fail to capture domain-specific features not prevalent in their training corpora. This paper introduces a residual learning approach that addresses this feature blindness without req... | [
"Nikita Koriagin",
"Yaroslav Aksenov",
"Daniil Laptev",
"Gleb Gerasimov",
"Nikita Balagansky",
"Daniil Gavrilov"
] | https://openreview.net/forum?id=d4XXFVAlV7 | d4XXFVAlV7 | d4XXFVAlV7 | [
"~Nikita_Koriagin1",
"~Yaroslav_Aksenov1",
"~Daniil_Laptev1",
"~Gleb_Gerasimov1",
"~Nikita_Balagansky3",
"~Daniil_Gavrilov1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/239b22ba90f8847d2c8c75fead3882620a2ec8d6.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM",
"Interpretability",
"SAE"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
koriagin2025teach,
title={Teach Old {SAE}s New Domain Tricks with Boosting},
author={Nikita Koriagin and Yaroslav Aksenov and Daniil Laptev and Gleb Gerasimov and Nikita Balagansky and Daniil Gavrilov},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id... | koriagin|teach_old_saes_new_domain_tricks_with_boosting | null | null | null | null | null | |
CultureCLIP: Empowering CLIP with Cultural Awareness through Synthetic Images and Contextualized Captions | We introduce CulTwin, a synthetic cultural dataset of visually similar concept pairs with contextualized captions, and CultureCLIP, a CLIP-based model fine-tuned to better distinguish visually similar yet culturally distinct concepts. | Pretrained vision-language models (VLMs) such as CLIP excel in general multimodal comprehension but often struggle to capture nuanced, context-dependent visual cues. This makes it difficult to distinguish between similar-looking concepts with potentially different cultural meanings. Such deficiencies are mainly due to ... | [
"Yuchen Huang",
"Zhiyuan Fan",
"Zhitao He",
"Sandeep Polisetty",
"Wenyan Li",
"Yi R. Fung"
] | https://openreview.net/forum?id=cWVpXWARbt | cWVpXWARbt | cWVpXWARbt | [
"~Yuchen_Huang4",
"~Zhiyuan_Fan2",
"~Zhitao_He1",
"~Sandeep_Polisetty1",
"~Wenyan_Li1",
"~Yi_R._Fung1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/43578f00390a568a2e3b91a5e2c0dd7ab5d002b7.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Vision-Language Models",
"Cultural Understanding",
"Fine-Grained Recognition",
"Contextual Knowledge",
"Synthetic Data Generation",
"Contrastive Learning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
huang2025cultureclip,
title={Culture{CLIP}: Empowering {CLIP} with Cultural Awareness through Synthetic Images and Contextualized Captions},
author={Yuchen Huang and Zhiyuan Fan and Zhitao He and Sandeep Polisetty and Wenyan Li and Yi R. Fung},
booktitle={Second Conference on Language Modeling},
year={2... | huang|cultureclip_empowering_clip_with_cultural_awareness_through_synthetic_images_and_contextualized_captions | null | null | null | null | null | |
Detecting and Pruning Prominent but Detrimental Neurons in Large Language Models | We fine-tune LLMs by pruning shortcut neurons using Integrated Gradients, improving generalization and performance on multiple-choice benchmarks. | Large language models (LLMs) often develop learned mechanisms specialized to specific datasets, such as reliance on domain-specific correlations, which yield high-confidence predictions without generalizable reasoning. While beneficial in one setting, these dataset-specific mechanisms typically degrade performance when... | [
"Ameen Ali Ali",
"Shahar Katz",
"Lior Wolf",
"Ivan Titov"
] | https://openreview.net/forum?id=cRE1XrHf1h | cRE1XrHf1h | cRE1XrHf1h | [
"~Ameen_Ali_Ali1",
"~Shahar_Katz1",
"~Lior_Wolf1",
"~Ivan_Titov1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/3e75fad4784de03c4f8695f26d4c0af5020dc3b9.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLMs",
"spurious correlations",
"Integrated Gradients",
"generalization",
"model adaptation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
ali2025detecting,
title={Detecting and Pruning Prominent but Detrimental Neurons in Large Language Models},
author={Ameen Ali Ali and Shahar Katz and Lior Wolf and Ivan Titov},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=cRE1XrHf1h}
} | ali|detecting_and_pruning_prominent_but_detrimental_neurons_in_large_language_models | /attachment/0f250681dff84bc33314f010f39c137641aa6d12.zip | null | null | null | null | |
Approximating Language Model Training Data from Weights | we recover suitable training data given only model weights | Modern language models often have open weights but closed training data. We formalize the problem of data recovery from model weights and propose several baselines and metrics. We develop a gradient-based approach that selects the highest-matching data from a large public text corpus and show its effectiveness at recov... | [
"John Xavier Morris",
"Junjie Oscar Yin",
"Woojeong Kim",
"Vitaly Shmatikov",
"Alexander M Rush"
] | https://openreview.net/forum?id=cQechnXCQt | cQechnXCQt | cQechnXCQt | [
"~John_Xavier_Morris1",
"~Junjie_Oscar_Yin1",
"~Woojeong_Kim1",
"~Vitaly_Shmatikov1",
"~Alexander_M_Rush1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/0566a6c6e8416f4fc6d0bedebfc25b7df8462f68.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"inversion",
"training data reconstruction"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
morris2025approximating,
title={Approximating Language Model Training Data from Weights},
author={John Xavier Morris and Junjie Oscar Yin and Woojeong Kim and Vitaly Shmatikov and Alexander M Rush},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=cQe... | morris|approximating_language_model_training_data_from_weights | null | null | null | null | null | |
Self-Rewarding PPO: Aligning Large Language Models with Demonstrations Only | We propose Self-Rewarding PPO, a novel fine-tuning method that combines the strengths of SFT and proximal policy optimization (PPO) to achieve more effective alignment from demonstration data. | Supervised fine-tuning (SFT) has emerged as a crucial method for aligning large language models (LLMs) with human-annotated demonstrations. However, SFT, being an off-policy approach similar to behavior cloning, often struggles with overfitting and poor out-of-domain generalization, especially in limited-data scenarios... | [
"Qingru Zhang",
"Liang Qiu",
"Ilgee Hong",
"Zhenghao Xu",
"Tianyi Liu",
"Shiyang Li",
"Rongzhi Zhang",
"Zheng Li",
"Lihong Li",
"Bing Yin",
"Chao Zhang",
"Jianshu Chen",
"Haoming Jiang",
"Tuo Zhao"
] | https://openreview.net/forum?id=cOlHP5E3qF | cOlHP5E3qF | cOlHP5E3qF | [
"~Qingru_Zhang2",
"~Liang_Qiu2",
"~Ilgee_Hong1",
"~Zhenghao_Xu1",
"~Tianyi_Liu2",
"~Shiyang_Li1",
"~Rongzhi_Zhang2",
"~Zheng_Li9",
"~Lihong_Li1",
"~Bing_Yin1",
"~Chao_Zhang15",
"~Jianshu_Chen1",
"~Haoming_Jiang1",
"~Tuo_Zhao2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c544f1212296d14078181345cb70fcb3f3316194.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Alignment with Demonstration",
"Self-Rewarding PPO",
"Large Language Models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhang2025selfrewarding,
title={Self-Rewarding {PPO}: Aligning Large Language Models with Demonstrations Only},
author={Qingru Zhang and Liang Qiu and Ilgee Hong and Zhenghao Xu and Tianyi Liu and Shiyang Li and Rongzhi Zhang and Zheng Li and Lihong Li and Bing Yin and Chao Zhang and Jianshu Chen and Hao... | zhang|selfrewarding_ppo_aligning_large_language_models_with_demonstrations_only | null | null | null | null | null | |
MS-SSM: A Multi-Scale State Space Model for Efficient Sequence Modeling | We introduce MS-SSM which enhances traditional SSMs by modeling sequence dynamics at multiple resolutions using independent SSMs, scale-dependent initialization, and an input-dependent scale-mixer. | State-space models (SSMs) have recently attention as an efficient alternative to computationally expensive attention-based models for sequence modeling. They rely on linear recurrences to integrate information over time, enabling fast inference, parallelizable training, and control over recurrence stability. However, ... | [
"Mahdi Karami",
"Ali Behrouz",
"Peilin Zhong",
"Razvan Pascanu",
"Vahab Mirrokni"
] | https://openreview.net/forum?id=cCYWeCzAv0 | cCYWeCzAv0 | cCYWeCzAv0 | [
"~Mahdi_Karami2",
"~Ali_Behrouz1",
"~Peilin_Zhong1",
"~Razvan_Pascanu1",
"~Vahab_Mirrokni2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/483868b1b70acb79914fb7e065ea71d3d5a37968.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"MS-SSM: Sequence Models",
"Language models",
"State Space Model",
"Multi-Scale",
"Multi-Resolution"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
karami2025msssm,
title={{MS}-{SSM}: A Multi-Scale State Space Model for Efficient Sequence Modeling},
author={Mahdi Karami and Ali Behrouz and Peilin Zhong and Razvan Pascanu and Vahab Mirrokni},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=cCYWeC... | karami|msssm_a_multiscale_state_space_model_for_efficient_sequence_modeling | null | null | null | null | null | |
DEL: Context-Aware Dynamic Exit Layer for Efficient Self-Speculative Decoding | We propose DEL, a dynamic method that adaptively selects the exit layer and speculation length in self-speculative decoding to accelerate large language model inference. | Speculative Decoding (SD) is a widely used approach to accelerate the inference of large language models (LLMs) without reducing generation quality. It operates by first using a compact model to draft multiple tokens efficiently, followed by parallel verification using the target LLM. This approach leads to faster infe... | [
"Hossein Entezari Zarch",
"Lei Gao",
"Chaoyi Jiang",
"Murali Annavaram"
] | https://openreview.net/forum?id=cAFxSuXQvT | cAFxSuXQvT | cAFxSuXQvT | [
"~Hossein_Entezari_Zarch1",
"~Lei_Gao3",
"~Chaoyi_Jiang1",
"~Murali_Annavaram1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e1dbcba837d14d0fa9c917359c3c5f0b9d4cb9d5.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Speculative Decoding",
"Efficient Large Language Model",
"Inference Acceleration"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zarch2025del,
title={{DEL}: Context-Aware Dynamic Exit Layer for Efficient Self-Speculative Decoding},
author={Hossein Entezari Zarch and Lei Gao and Chaoyi Jiang and Murali Annavaram},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=cAFxSuXQvT}
} | zarch|del_contextaware_dynamic_exit_layer_for_efficient_selfspeculative_decoding | null | null | null | null | null | |
LLMs Are In-Context Bandit Reinforcement Learners | LLMs can learn in-context from online rewards like in reinforcement learning, instead of just supervised examples | Large Language Models (LLMs) excel at in-context learning (ICL), a supervised learning technique that relies on adding annotated examples to the model context. We investigate a contextual bandit version of in-context reinforcement learning (ICRL), where models learn in-context, online, from external reward, instead of ... | [
"Giovanni Monea",
"Antoine Bosselut",
"Kianté Brantley",
"Yoav Artzi"
] | https://openreview.net/forum?id=c0RsezY2D1 | c0RsezY2D1 | c0RsezY2D1 | [
"~Giovanni_Monea1",
"~Antoine_Bosselut1",
"~Kianté_Brantley2",
"~Yoav_Artzi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/628804cb3e9ad8568125424f3e5621da8ba4504d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"In-context reinforcement learning",
"in-context learning",
"contextual bandits",
"online learning",
"large language models"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
monea2025llms,
title={{LLM}s Are In-Context Bandit Reinforcement Learners},
author={Giovanni Monea and Antoine Bosselut and Kiant{\'e} Brantley and Yoav Artzi},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=c0RsezY2D1}
} | monea|llms_are_incontext_bandit_reinforcement_learners | /attachment/856e277943bbf727353282951700d1741ae0833b.zip | null | null | null | null | |
Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning | We introduce a unified architecture that pauses autoregressive text generation for latent diffusion planning, enabling higher quality and more controllable text generation with improved language understanding. | The Stop-Think-AutoRegress Language Diffusion Model (STAR-LDM) integrates latent diffusion planning with autoregressive generation. Unlike conventional autoregressive language models limited to token-by-token decisions, STAR-LDM incorporates a ``thinking'' phase that pauses generation to refine a semantic plan through ... | [
"Justin Lovelace",
"Christian K Belardi",
"Sofian Zalouk",
"Adhitya Polavaram",
"Srivatsa R Kundurthy",
"Kilian Q Weinberger"
] | https://openreview.net/forum?id=c05qIG1Z2B | c05qIG1Z2B | c05qIG1Z2B | [
"~Justin_Lovelace1",
"~Christian_K_Belardi1",
"~Sofian_Zalouk1",
"~Adhitya_Polavaram1",
"~Srivatsa_R_Kundurthy1",
"~Kilian_Q_Weinberger1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/a567037e14bb0b772ee2dbb773ee14c211a329eb.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"diffusion",
"latent diffusion",
"language generation"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lovelace2025stopthinkautoregress,
title={Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning},
author={Justin Lovelace and Christian K Belardi and Sofian Zalouk and Adhitya Polavaram and Srivatsa R Kundurthy and Kilian Q Weinberger},
booktitle={Second Conference on Language Modeling... | lovelace|stopthinkautoregress_language_modeling_with_latent_diffusion_planning | null | null | null | null | null | |
Yourbench: Dynamic Evaluation Set Generation with LLMs | a new system to generate diverse question answers from source documents ensuring maximum document coverage | Large language models (LLMs) have rapidly outpaced traditional evaluation methodologies, with static benchmarks suffering from saturation, contamination, and domain-specificity limitations while human evaluation remains prohibitively expensive. We present YourBench, an open-source framework that transforms this evaluat... | [
"Sumuk Shashidhar",
"Clémentine Fourrier",
"Alina Lozovskaya",
"Thomas Wolf",
"Gokhan Tur",
"Dilek Hakkani-Tür"
] | https://openreview.net/forum?id=bkWERVKzuP | bkWERVKzuP | bkWERVKzuP | [
"~Sumuk_Shashidhar1",
"~Clémentine_Fourrier1",
"~Alina_Lozovskaya1",
"~Thomas_Wolf1",
"~Gokhan_Tur2",
"~Dilek_Hakkani-Tür1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/a24fd7f123f1ad2093ae9bd1a7d79ae8e52f2822.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"benchmarking",
"contemporary dataset",
"dataset",
"reference-free",
"automated",
"llm"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
shashidhar2025yourbench,
title={Yourbench: Dynamic Evaluation Set Generation with {LLM}s},
author={Sumuk Shashidhar and Cl{\'e}mentine Fourrier and Alina Lozovskaya and Thomas Wolf and Gokhan Tur and Dilek Hakkani-T{\"u}r},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://op... | shashidhar|yourbench_dynamic_evaluation_set_generation_with_llms | /attachment/6f599491b12fd956502386d694a034247fe66463.zip | null | null | null | null | |
Hawkeye: Model Collaboration for Efficient Reasoning | We provide an efficient inference pipeline that optimizes Chain-of-Thought (CoT) reasoning by instructing a Large Language Model (LLM) to generate concise yet effective CoTs for a Small Language Model (SLM) to decode through reinforcement learning. | Chain-of-Thought (CoT) reasoning has demonstrated remarkable effectiveness in enhancing the reasoning abilities of large language models (LLMs). However, its efficiency remains a challenge due to excessive intermediate reasoning tokens, which introduce both semantic redundancy and unnecessarily detailed reasoning steps... | [
"Jianshu She",
"Zhuohao Li",
"Zhemin Huang",
"Qi Li",
"Peiran Xu",
"Haonan Li",
"Qirong Ho"
] | https://openreview.net/forum?id=bdCWK4NkK7 | bdCWK4NkK7 | bdCWK4NkK7 | [
"~Jianshu_She1",
"~Zhuohao_Li3",
"~Zhemin_Huang1",
"~Qi_Li39",
"~Peiran_Xu2",
"~Haonan_Li2",
"~Qirong_Ho1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/1e689a967422ea14219cc7b7d5e1234d934f7ed1.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"reinforcement learning (with human feedback)",
"fine-tuning",
"compression",
"decoding algorithms",
"reasoning algorithms"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
she2025hawkeye,
title={Hawkeye: Model Collaboration for Efficient Reasoning},
author={Jianshu She and Zhuohao Li and Zhemin Huang and Qi Li and Peiran Xu and Haonan Li and Qirong Ho},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=bdCWK4NkK7}
} | she|hawkeye_model_collaboration_for_efficient_reasoning | null | null | null | null | null | |
LoRe: Personalizing LLMs via Low-Rank Reward Modeling | We introduce low-rank personalized preference modeling for LLMs, enabling scalable and efficient user-specific reward learning with superior generalization and few-shot adaptation. | Personalizing large language models (LLMs) to accommodate diverse user preferences is essential for enhancing alignment and user satisfaction. Traditional reinforcement learning from human feedback (RLHF) approaches often rely on monolithic value representations, limiting their ability to adapt to individual preference... | [
"Avinandan Bose",
"Zhihan Xiong",
"Yuejie Chi",
"Simon Shaolei Du",
"Lin Xiao",
"Maryam Fazel"
] | https://openreview.net/forum?id=bYu4DOqRY8 | bYu4DOqRY8 | bYu4DOqRY8 | [
"~Avinandan_Bose1",
"~Zhihan_Xiong1",
"~Yuejie_Chi1",
"~Simon_Shaolei_Du1",
"~Lin_Xiao1",
"~Maryam_Fazel1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/350a08ec6b099c62f340e25b0560b73653f3a110.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"preference learning",
"personalization",
"reward modeling",
"plurality"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
bose2025lore,
title={LoRe: Personalizing {LLM}s via Low-Rank Reward Modeling},
author={Avinandan Bose and Zhihan Xiong and Yuejie Chi and Simon Shaolei Du and Lin Xiao and Maryam Fazel},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=bYu4DOqRY8}
} | bose|lore_personalizing_llms_via_lowrank_reward_modeling | /attachment/378b641524b06586290a0a9e85ffb9de08e61924.zip | null | null | null | null | |
The Dual-Route Model of Induction | We find that LLMs can do in-context copying in two different ways: either by copying individual tokens verbatim, or by copying entire word meanings (which may span multiple tokens). | Prior work on in-context copying has shown the existence of *induction heads*, which attend to and promote individual tokens during copying. In this work we discover a new type of induction head: *concept-level* induction heads, which copy entire lexical units instead of individual tokens. Concept induction heads learn... | [
"Sheridan Feucht",
"Eric Todd",
"Byron C Wallace",
"David Bau"
] | https://openreview.net/forum?id=bNTrKqqnG9 | bNTrKqqnG9 | bNTrKqqnG9 | [
"~Sheridan_Feucht1",
"~Eric_Todd1",
"~Byron_C_Wallace1",
"~David_Bau1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/44805a940b65757f691cc13691a90581dcdb453a.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"interpretability",
"induction heads",
"in-context learning",
"ICL",
"detokenization"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
feucht2025the,
title={The Dual-Route Model of Induction},
author={Sheridan Feucht and Eric Todd and Byron C Wallace and David Bau},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=bNTrKqqnG9}
} | feucht|the_dualroute_model_of_induction | null | null | null | null | null | |
CrossWordBench: Evaluating the Reasoning Capabilities of LLMs and LVLMs with Controllable Puzzle Generation | We propose CrossWordBench, a benchmark to evaluate the reasoning capabilities of both LLMs and LVLMs though the medium of crossword puzzles. | Existing reasoning evaluation frameworks for Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) predominantly assess either text-based reasoning or vision-language understanding capabilities, with limited dynamic interplay between textual and visual constraints. To address this limitation, we introdu... | [
"Jixuan Leng",
"Chengsong Huang",
"Langlin Huang",
"Bill Yuchen Lin",
"William W. Cohen",
"Haohan Wang",
"Jiaxin Huang"
] | https://openreview.net/forum?id=bJCQMKwPVq | bJCQMKwPVq | bJCQMKwPVq | [
"~Jixuan_Leng1",
"~Chengsong_Huang1",
"~Langlin_Huang1",
"~Bill_Yuchen_Lin1",
"~William_W._Cohen2",
"~Haohan_Wang1",
"~Jiaxin_Huang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/4387a92ca259f0b87c9d01fd2c80a1dd97ba0084.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLMs",
"LVLMs",
"Evaluation",
"Benchmark"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
leng2025crosswordbench,
title={CrossWordBench: Evaluating the Reasoning Capabilities of {LLM}s and {LVLM}s with Controllable Puzzle Generation},
author={Jixuan Leng and Chengsong Huang and Langlin Huang and Bill Yuchen Lin and William W. Cohen and Haohan Wang and Jiaxin Huang},
booktitle={Second Confere... | leng|crosswordbench_evaluating_the_reasoning_capabilities_of_llms_and_lvlms_with_controllable_puzzle_generation | null | null | null | null | null | |
From Next-Token to Mathematics: The Learning Dynamics of Mathematical Reasoning in Language Models | We conduct the first analysis of how math reasoning skills are learned during pre- and post-training using open checkpoint and open weight models. | Large Language Models (LLMs) solely trained on next-token prediction learn to solve a wide range of problems involving mathematical reasoning. How does this ability evolve during training? We show the first analysis of how mathematical reasoning abilities of several open-weight LLMs develop during pre-training and post... | [
"Shubhra Mishra",
"Gabriel Poesia",
"Noah Goodman"
] | https://openreview.net/forum?id=bJ9aARjtBu | bJ9aARjtBu | bJ9aARjtBu | [
"~Shubhra_Mishra1",
"~Gabriel_Poesia1",
"~Noah_Goodman1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/af194ebe55dcf8e07919154014cfe0ed016dd5db.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"math reasoning",
"training dynamics",
"reasoning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
mishra2025from,
title={From Next-Token to Mathematics: The Learning Dynamics of Mathematical Reasoning in Language Models},
author={Shubhra Mishra and Gabriel Poesia and Noah Goodman},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=bJ9aARjtBu}
} | mishra|from_nexttoken_to_mathematics_the_learning_dynamics_of_mathematical_reasoning_in_language_models | null | null | null | null | null | |
LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation | LoRI is a simple yet effective method for parameter-efficient fine-tuning that reduces cross-task interference by freezing projection matrices $A$ and sparsifying $B$. | Low-Rank Adaptation (LoRA) has emerged as a popular parameter-efficient fine-tuning (PEFT) method for Large Language Models (LLMs), yet it still incurs notable overhead and suffers from parameter interference in multi-task scenarios. We propose LoRA with Reduced Interference (LoRI), a simple yet effective approach that... | [
"Juzheng Zhang",
"Jiacheng You",
"Ashwinee Panda",
"Tom Goldstein"
] | https://openreview.net/forum?id=b8cW86QcOD | b8cW86QcOD | b8cW86QcOD | [
"~Juzheng_Zhang2",
"~Jiacheng_You1",
"~Ashwinee_Panda1",
"~Tom_Goldstein1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/31e650897c20dd83f40dca4cf8678bd5c44bdfac.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Parameter-Efficient Fine-Tuning",
"Model Merging",
"Sparsity"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zhang2025lori,
title={Lo{RI}: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation},
author={Juzheng Zhang and Jiacheng You and Ashwinee Panda and Tom Goldstein},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=b8cW86QcOD}
} | zhang|lori_reducing_crosstask_interference_in_multitask_lowrank_adaptation | null | null | null | null | null | |
OpenCodeReasoning: Advancing Data Distillation for Competitive Coding | We construct, analyze and release a curated code reasoning dataset of 735K samples that instills SOTA reasoning capabilities, evaluated on LiveCodeBench. | Since the advent of reasoning-based large language models, many have found great success from distilling reasoning capabilities into student models. Such techniques have significantly bridged the gap between reasoning and standard LLMs on coding tasks. Despite this, much of the progress on distilling reasoning models r... | [
"Wasi Uddin Ahmad",
"Sean Narenthiran",
"Somshubra Majumdar",
"Aleksander Ficek",
"Siddhartha Jain",
"Jocelyn Huang",
"Vahid Noroozi",
"Boris Ginsburg"
] | https://openreview.net/forum?id=aykM7KUVJZ | aykM7KUVJZ | aykM7KUVJZ | [
"~Wasi_Uddin_Ahmad1",
"~Sean_Narenthiran1",
"~Somshubra_Majumdar1",
"~Aleksander_Ficek1",
"~Siddhartha_Jain1",
"~Jocelyn_Huang1",
"~Vahid_Noroozi2",
"~Boris_Ginsburg1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/544a715a36130a61830a4ddadb3420047cc5cf02.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Code Generation",
"Code Reasoning",
"Large Language Model",
"LiveCodeBench"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
ahmad2025opencodereasoning,
title={OpenCodeReasoning: Advancing Data Distillation for Competitive Coding},
author={Wasi Uddin Ahmad and Sean Narenthiran and Somshubra Majumdar and Aleksander Ficek and Siddhartha Jain and Jocelyn Huang and Vahid Noroozi and Boris Ginsburg},
booktitle={Second Conference o... | ahmad|opencodereasoning_advancing_data_distillation_for_competitive_coding | null | null | null | null | null | |
PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling | We developed PyramidKV, a novel and effective KV cache compression method. | In this study, we investigate whether attention-based information flow inside large language models (LLMs) is aggregated through noticeable patterns for long context processing. Our observations reveal that LLMs aggregate information through Pyramidal Information Funneling where attention is scattering widely in lower ... | [
"Zefan Cai",
"Yichi Zhang",
"Bofei Gao",
"Yuliang Liu",
"Yucheng Li",
"Tianyu Liu",
"Keming Lu",
"Wayne Xiong",
"Yue Dong",
"Junjie Hu",
"Wen Xiao"
] | https://openreview.net/forum?id=ayi7qezU87 | ayi7qezU87 | ayi7qezU87 | [
"~Zefan_Cai1",
"~Yichi_Zhang16",
"~Bofei_Gao1",
"~Yuliang_Liu5",
"~Yucheng_Li5",
"~Tianyu_Liu3",
"~Keming_Lu1",
"~Wayne_Xiong1",
"~Yue_Dong2",
"~Junjie_Hu2",
"~Wen_Xiao2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/40900f3b1b3442ab76c9934ef2acc1c2a3ebb3e5.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"KV Cache Compression",
"Inference Acceleration"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
cai2025pyramidkv,
title={Pyramid{KV}: Dynamic {KV} Cache Compression based on Pyramidal Information Funneling},
author={Zefan Cai and Yichi Zhang and Bofei Gao and Yuliang Liu and Yucheng Li and Tianyu Liu and Keming Lu and Wayne Xiong and Yue Dong and Junjie Hu and Wen Xiao},
booktitle={Second Conferen... | cai|pyramidkv_dynamic_kv_cache_compression_based_on_pyramidal_information_funneling | null | true | null | null | null | |
RWKV-7 "Goose" with Expressive Dynamic State Evolution | RWKV-7 is a new sequence modeling architecture with constant memory usage and inference time per token, SoTA performance on multilingual tasks, and near SoTA English LLM performance at 3B scale, with dramatically less training than top 3B models. | We present RWKV-7 "Goose", a new sequence modeling architecture with constant memory usage and constant inference time per token. Despite being trained on dramatically fewer tokens than other top models, our 2.9 billion parameter language model achieves a new 3B SoTA on multilingual tasks and matches the current 3B SoT... | [
"Bo Peng",
"Ruichong Zhang",
"Daniel Goldstein",
"Eric Alcaide",
"Xingjian Du",
"Haowen Hou",
"Jiaju Lin",
"Jiaxing Liu",
"Janna Lu",
"William Merrill",
"Guangyu Song",
"Kaifeng Tan",
"Saiteja Utpala",
"Nathan Wilce",
"Johan S. Wind",
"Tianyi Wu",
"Daniel Wuttke",
"Christian Zhou-Z... | https://openreview.net/forum?id=ayB1PACN5j | ayB1PACN5j | ayB1PACN5j | [
"~Bo_Peng21",
"~Ruichong_Zhang1",
"~Daniel_Goldstein2",
"~Eric_Alcaide2",
"~Xingjian_Du1",
"~Haowen_Hou2",
"~Jiaju_Lin1",
"~Jiaxing_Liu2",
"~Janna_Lu1",
"~William_Merrill1",
"~Guangyu_Song1",
"~Kaifeng_Tan1",
"~Saiteja_Utpala1",
"~Nathan_Wilce1",
"~Johan_S._Wind2",
"~Tianyi_Wu11",
"~... | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/74011cffc1082ac9394afde92802c810c51baabf.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Goose",
"LLM",
"RWKV",
"RWKV-7",
"RWKV7",
"Linear",
"Linear Attention",
"SSM",
"subquadratic"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
peng2025rwkv,
title={{RWKV}-7 ''Goose'' with Expressive Dynamic State Evolution},
author={Bo Peng and Ruichong Zhang and Daniel Goldstein and Eric Alcaide and Xingjian Du and Haowen Hou and Jiaju Lin and Jiaxing Liu and Janna Lu and William Merrill and Guangyu Song and Kaifeng Tan and Saiteja Utpala and... | peng|rwkv7_goose_with_expressive_dynamic_state_evolution | null | null | null | null | null | |
Navigating the Rabbit Hole: Emergent Biases in LLM-Generated Attack Narratives Targeting Mental Health Groups | We propose a framework to analyze the disproportionate targeting of mental health groups in LLM-generated attack chains. | Large Language Models (LLMs) have been shown to demonstrate imbalanced biases against certain groups. However, the study of unprovoked targeted attacks by LLMs towards at-risk populations remains underexplored. Our paper presents three novel contributions: (1) the explicit evaluation of LLM-generated attacks on highly ... | [
"Rijul Magu",
"Arka Dutta",
"Sean Kim",
"Ashiqur R. KhudaBukhsh",
"Munmun De Choudhury"
] | https://openreview.net/forum?id=am6p8VFm9l | am6p8VFm9l | am6p8VFm9l | [
"~Rijul_Magu1",
"~Arka_Dutta2",
"~Sean_Kim2",
"~Ashiqur_R._KhudaBukhsh1",
"~Munmun_De_Choudhury1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/1b19b81748a05fae5824c5d1f9c1564132c741c6.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Mental Health",
"Network Analysis",
"Stigmatization",
"Emergent Bias",
"Toxicity"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
magu2025navigating,
title={Navigating the Rabbit Hole: Emergent Biases in {LLM}-Generated Attack Narratives Targeting Mental Health Groups},
author={Rijul Magu and Arka Dutta and Sean Kim and Ashiqur R. KhudaBukhsh and Munmun De Choudhury},
booktitle={Second Conference on Language Modeling},
year={2025}... | magu|navigating_the_rabbit_hole_emergent_biases_in_llmgenerated_attack_narratives_targeting_mental_health_groups | null | null | null | null | null | |
CLIPPER: Compression enables long-context synthetic data generation | We introduce CLIPPER, a compression-based approach for generating synthetic data tailored to narrative claim verification—a task that requires reasoning over a book to verify a given claim. | LLM developers are increasingly reliant on synthetic data, but generating high-quality data for complex long-context reasoning tasks remains challenging. We introduce CLIPPER, a compression-based approach for generating synthetic data tailored to narrative claim verification—a task that requires reasoning over a book t... | [
"Chau Minh Pham",
"Yapei Chang",
"Mohit Iyyer"
] | https://openreview.net/forum?id=akHq1QcqeZ | akHq1QcqeZ | akHq1QcqeZ | [
"~Chau_Minh_Pham1",
"~Yapei_Chang1",
"~Mohit_Iyyer1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/f2024d79618cdeeb40b50c0b1836ce0cee87c511.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"synthetic data",
"fine-tuning",
"instruction-tuning"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
pham2025clipper,
title={{CLIPPER}: Compression enables long-context synthetic data generation},
author={Chau Minh Pham and Yapei Chang and Mohit Iyyer},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=akHq1QcqeZ}
} | pham|clipper_compression_enables_longcontext_synthetic_data_generation | null | null | null | null | null | |
EvalTree: Profiling Language Model Weaknesses via Hierarchical Capability Trees | Formulating the problem of LM weakness profiling and proposing a method EvalTree | An ideal model evaluation should achieve two goals: identifying where the model fails and providing actionable improvement guidance. Toward these goals for language model (LM) evaluations, we formulate the problem of generating a weakness profile, a set of weaknesses expressed in natural language, given an LM's perform... | [
"Zhiyuan Zeng",
"Yizhong Wang",
"Hannaneh Hajishirzi",
"Pang Wei Koh"
] | https://openreview.net/forum?id=aV2hQN9vkp | aV2hQN9vkp | aV2hQN9vkp | [
"~Zhiyuan_Zeng3",
"~Yizhong_Wang2",
"~Hannaneh_Hajishirzi1",
"~Pang_Wei_Koh1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/64efd69a5024b2582a5aca08978a2cae631b8b00.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Evaluation",
"Interpretability"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
zeng2025evaltree,
title={EvalTree: Profiling Language Model Weaknesses via Hierarchical Capability Trees},
author={Zhiyuan Zeng and Yizhong Wang and Hannaneh Hajishirzi and Pang Wei Koh},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=aV2hQN9vkp}
} | zeng|evaltree_profiling_language_model_weaknesses_via_hierarchical_capability_trees | null | null | null | null | null | |
Shared Global and Local Geometry of Language Model Embeddings | We characterize the global and local geometry of language model token embeddings and find similarities across language models. | Researchers have recently suggested that models share common representations. In our work, we find numerous geometric similarities across the token embeddings of large language models. First, we find “global” similarities: token embeddings often share similar relative orientations. Next, we characterize local geometry ... | [
"Andrew Lee",
"Melanie Weber",
"Fernanda Viégas",
"Martin Wattenberg"
] | https://openreview.net/forum?id=aJDykpJAYF | aJDykpJAYF | aJDykpJAYF | [
"~Andrew_Lee2",
"~Melanie_Weber1",
"~Fernanda_Viégas1",
"~Martin_Wattenberg1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/3cb8501d114bc2f5dbfc0cb0be5bdffcc5d4d3e1.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Embeddings",
"Alignment",
"Interpretability"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
lee2025shared,
title={Shared Global and Local Geometry of Language Model Embeddings},
author={Andrew Lee and Melanie Weber and Fernanda Vi{\'e}gas and Martin Wattenberg},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=aJDykpJAYF}
} | lee|shared_global_and_local_geometry_of_language_model_embeddings | null | true | null | null | null | |
Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF | We provide a novel active learning method for RLHF based on the Sharpe Ratio. | Reinforcement learning from human feedback (RLHF) has become a cornerstone of the training and alignment pipeline for large language models (LLMs). Recent advances, such as direct preference optimization (DPO), have simplified the preference learning step. However, collecting preference data remains a challenging and c... | [
"Syrine Belakaria",
"Joshua Kazdan",
"Charles Marx",
"Chris Cundy",
"Willie Neiswanger",
"Sanmi Koyejo",
"Barbara E Engelhardt",
"Stefano Ermon"
] | https://openreview.net/forum?id=a6xzTqMUFQ | a6xzTqMUFQ | a6xzTqMUFQ | [
"~Syrine_Belakaria1",
"~Joshua_Kazdan1",
"~Charles_Marx1",
"~Chris_Cundy1",
"~Willie_Neiswanger2",
"~Sanmi_Koyejo1",
"~Barbara_Engelhardt1",
"~Stefano_Ermon1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/25abf5aa983f29b83734f87acba47b58d8e8c5f6.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"active learning",
"RLHF",
"llm"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
belakaria2025sharpe,
title={Sharpe Ratio-Guided Active Learning for Preference Optimization in {RLHF}},
author={Syrine Belakaria and Joshua Kazdan and Charles Marx and Chris Cundy and Willie Neiswanger and Sanmi Koyejo and Barbara E Engelhardt and Stefano Ermon},
booktitle={Second Conference on Language... | belakaria|sharpe_ratioguided_active_learning_for_preference_optimization_in_rlhf | null | null | null | null | null | |
Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs | We study how respecting web crawling opt-outs (robots.txt) affects LLM performance by introducing the concept of Data Compliance Gap (DCG). | The increasing adoption of web crawling opt-outs by copyright holders of online content raises critical questions about the impact of data compliance on large language model (LLM) performance. However, little is known about how these restrictions (and the resultant filtering of pretraining datasets) affect the capabili... | [
"Dongyang Fan",
"Vinko Sabolčec",
"Matin Ansaripour",
"Ayush Kumar Tarun",
"Martin Jaggi",
"Antoine Bosselut",
"Imanol Schlag"
] | https://openreview.net/forum?id=a6QsOjr3wo | a6QsOjr3wo | a6QsOjr3wo | [
"~Dongyang_Fan2",
"~Vinko_Sabolčec1",
"~Matin_Ansaripour1",
"~Ayush_Kumar_Tarun1",
"~Martin_Jaggi1",
"~Antoine_Bosselut1",
"~Imanol_Schlag3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c04ef11771a5e838ccf85b71b78636ed913f5ae0.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Responsible AI",
"AI and Fair Use",
"Robots.txt Opt-out",
"LLMs"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
fan2025can,
title={Can Performant {LLM}s Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs},
author={Dongyang Fan and Vinko Sabol{\v{c}}ec and Matin Ansaripour and Ayush Kumar Tarun and Martin Jaggi and Antoine Bosselut and Imanol Schlag},
booktitle={Second Conference on Language Modeling},
ye... | fan|can_performant_llms_be_ethical_quantifying_the_impact_of_web_crawling_optouts | null | null | null | null | null | |
Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression | Using interpretability informed saliency scores based on task-specific information to localize important weights to preserve during model compression, yielding SOTA method for both general and task specific quantization | Post-training quantization reduces a model's memory footprint by mapping full precision weights into low bit weights without costly retraining, but can degrade its downstream performance especially in low 2- to 3-bit settings. Existing methods mitigate these drops by keeping some important weights in higher precision... | [
"Hanqi Xiao",
"Yi-Lin Sung",
"Elias Stengel-Eskin",
"Mohit Bansal"
] | https://openreview.net/forum?id=a201nfn3xX | a201nfn3xX | a201nfn3xX | [
"~Hanqi_Xiao1",
"~Yi-Lin_Sung1",
"~Elias_Stengel-Eskin1",
"~Mohit_Bansal2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e79023ddb144530c26e3752115728796c7dc13cb.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Quantization",
"Mixed Precision",
"Interpretability"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
xiao2025taskcircuit,
title={Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression},
author={Hanqi Xiao and Yi-Lin Sung and Elias Stengel-Eskin and Mohit Bansal},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum... | xiao|taskcircuit_quantization_leveraging_knowledge_localization_and_interpretability_for_compression | null | null | null | null | null | |
Rethinking Safety in LLM Fine-tuning: An Optimization Perspective | Fine-tuning can preserve safety without extra interventions by optimizing hyperparameters and using EMA momentum to stabilize training. | Fine-tuning language models is commonly believed to inevitably harm their safety, i.e., refusing to respond to harmful user requests, even when using harmless datasets, thus requiring additional safety measures.
We challenge this belief through systematic testing, showing that poor optimization choices, rather than inh... | [
"Minseon Kim",
"Jin Myung Kwak",
"Lama Alssum",
"Bernard Ghanem",
"Philip Torr",
"David Krueger",
"Fazl Barez",
"Adel Bibi"
] | https://openreview.net/forum?id=ZnOoEA2nDn | ZnOoEA2nDn | ZnOoEA2nDn | [
"~Minseon_Kim1",
"~Jin_Myung_Kwak1",
"~Lama_Alssum1",
"~Bernard_Ghanem1",
"~Philip_Torr1",
"~David_Krueger1",
"~Fazl_Barez1",
"~Adel_Bibi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/69c14ab3b7570c1351454fdff6e3989c37b2932d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Finetuning LLM",
"Safety alignment"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
kim2025rethinking,
title={Rethinking Safety in {LLM} Fine-tuning: An Optimization Perspective},
author={Minseon Kim and Jin Myung Kwak and Lama Alssum and Bernard Ghanem and Philip Torr and David Krueger and Fazl Barez and Adel Bibi},
booktitle={Second Conference on Language Modeling},
year={2025},
url=... | kim|rethinking_safety_in_llm_finetuning_an_optimization_perspective | null | null | null | null | null | |
Hell or High Water: Evaluating Agentic Recovery from External Failures | Evaluating how well LLMs can find backup plans | As language model agents are applied to real world problems of increasing complexity, they will be expected to formulate plans across large search spaces. If those plans fail for reasons beyond their control, how well do language agents search for alternative ways to achieve their goals? We devise a specialized agentic... | [
"Andrew Wang",
"Sophia Hager",
"Adi Asija",
"Daniel Khashabi",
"Nicholas Andrews"
] | https://openreview.net/forum?id=Zk224WPT42 | Zk224WPT42 | Zk224WPT42 | [
"~Andrew_Wang3",
"~Sophia_Hager1",
"~Adi_Asija1",
"~Daniel_Khashabi2",
"~Nicholas_Andrews2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/30827c25a31a17f74cbb9a570f0d6f26a95ad034.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"planning",
"tool-use"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
wang2025hell,
title={Hell or High Water: Evaluating Agentic Recovery from External Failures},
author={Andrew Wang and Sophia Hager and Adi Asija and Daniel Khashabi and Nicholas Andrews},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=Zk224WPT42}
} | wang|hell_or_high_water_evaluating_agentic_recovery_from_external_failures | null | null | null | null | null | |
Do LLMs Understand Your Translations? Evaluating Paragraph-level MT with Question Answering | An extrinsic approach to evaluate long translations, using LLMs to generate and answer reading comprehension questions. | Despite the steady progress in machine translation evaluation, existing automatic metrics struggle to capture how well meaning is preserved beyond sentence boundaries. We posit that reliance on a single intrinsic quality score, trained to mimic human judgments, might be insufficient for evaluating translations of long,... | [
"Patrick Fernandes",
"Sweta Agrawal",
"Emmanouil Zaranis",
"Andre Martins",
"Graham Neubig"
] | https://openreview.net/forum?id=Zfa9jCYGCz | Zfa9jCYGCz | Zfa9jCYGCz | [
"~Patrick_Fernandes1",
"~Sweta_Agrawal1",
"~Emmanouil_Zaranis1",
"~Andre_Martins1",
"~Graham_Neubig1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e337466478c0587324eac3059bdd874f58d81acd.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"llm-based metric",
"machine translation",
"evaluation",
"question generation",
"question answering"
] | I acknowledge that I and all co-authors of this work have read and commit to adhering to the COLM Code of Ethics on https://colmweb.org/CoE.html | I certify that this submission complies with the submission instructions as described on https://colmweb.org/AuthorGuide.html | null | null | @inproceedings{
fernandes2025do,
title={Do {LLM}s Understand Your Translations? Evaluating Paragraph-level {MT} with Question Answering},
author={Patrick Fernandes and Sweta Agrawal and Emmanouil Zaranis and Andre Martins and Graham Neubig},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://... | fernandes|do_llms_understand_your_translations_evaluating_paragraphlevel_mt_with_question_answering | null | null | null | null | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.