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Jigsaw Puzzles: Splitting Harmful Questions to Jailbreak Large Language Models in Multi-turn Interactions | In this work, we propose Jigsaw Puzzles (JSP), a straightforward yet effective multi-turn jailbreak strategy, exposing LLM vulnerabilities to inform future safety improvements. | Large language models (LLMs) have exhibited outstanding performance in engaging with humans and addressing complex questions by leveraging their vast implicit knowledge and robust reasoning capabilities. However, such models are vulnerable to jailbreak attacks, leading to the generation of harmful responses. Despite re... | [
"Hao Yang",
"Lizhen Qu",
"Ehsan Shareghi",
"Gholamreza Haffari"
] | https://openreview.net/forum?id=zuNM3eoPVi | zuNM3eoPVi | zuNM3eoPVi | [
"~Hao_Yang26",
"~Lizhen_Qu2",
"~Ehsan_Shareghi1",
"~Gholamreza_Haffari2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/37b5d26cf61599e9f7a4d742ff910b1026aec236.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Jailbreak",
"Red teaming"
] | 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 | Does not discuss potentially harmful ramifications and dual use
| @inproceedings{
yang2025jigsaw,
title={Jigsaw Puzzles: Splitting Harmful Questions to Jailbreak Large Language Models in Multi-turn Interactions},
author={Hao Yang and Lizhen Qu and Ehsan Shareghi and Gholamreza Haffari},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum... | yang|jigsaw_puzzles_splitting_harmful_questions_to_jailbreak_large_language_models_in_multiturn_interactions | null | null | null | null | null | |
Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents | State-of-the-art results on Computer Use using a framework of Generalist and Specialist modules. | Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering significant potential to enhance human productivity by completing an open-ended space of user queries. However, current agents face significant challenges: imprecise groundi... | [
"Saaket Agashe",
"Kyle Wong",
"Vincent Tu",
"Jiachen Yang",
"Ang Li",
"Xin Eric Wang"
] | https://openreview.net/forum?id=zg5is4GJ3R | zg5is4GJ3R | zg5is4GJ3R | [
"~Saaket_Agashe1",
"~Kyle_Wong1",
"~Vincent_Tu1",
"~Jiachen_Yang1",
"~Ang_Li1",
"~Xin_Eric_Wang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/51a372ef953dfccf2d22d4657f707fe1bf9383b2.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Computer Use",
"GUI Agents",
"Multimodal Large Language Models",
"Planning",
"Grounding",
"Vision"
] | 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{
agashe2025agent,
title={Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents},
author={Saaket Agashe and Kyle Wong and Vincent Tu and Jiachen Yang and Ang Li and Xin Eric Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/foru... | agashe|agent_s2_a_compositional_generalistspecialist_framework_for_computer_use_agents | /attachment/ecc357b402b416c7ea4804242770e4c521a46cfd.zip | null | null | null | null | |
GenerationPrograms: Fine-grained Attribution with Executable Programs | GenerationPrograms: Fine-grained Attribution via Neural Modular Trees | Recent large language models (LLMs) achieve impressive performance in text generation but often fail to accurately attribute their outputs, undermining trust and verifiability. Moreover, existing attribution methods do not explain how and why models leverage the provided source documents to generate their final respons... | [
"David Wan",
"Eran Hirsch",
"Elias Stengel-Eskin",
"Ido Dagan",
"Mohit Bansal"
] | https://openreview.net/forum?id=zTKYKiWzIm | zTKYKiWzIm | zTKYKiWzIm | [
"~David_Wan1",
"~Eran_Hirsch1",
"~Elias_Stengel-Eskin1",
"~Ido_Dagan1",
"~Mohit_Bansal2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/879c600a2233a7fa325b3ccd7a81cd7277332584.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"long-form qa",
"rag",
"summarization",
"attributed text 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{
wan2025generationprograms,
title={GenerationPrograms: Fine-grained Attribution with Executable Programs},
author={David Wan and Eran Hirsch and Elias Stengel-Eskin and Ido Dagan and Mohit Bansal},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=zTKY... | wan|generationprograms_finegrained_attribution_with_executable_programs | /attachment/22e800fcc6dc11a936f21b1f04a507d404c9515d.zip | null | null | null | null | |
Can A Society of Generative Agents Simulate Human Behavior and Inform Public Health Policy? A Case Study on Vaccine Hesitancy | Investigate if a multi LLM agent system can simulate human health behaviors and inform policymaking. | Can we simulate a sandbox society with generative agents to model human behavior, thereby reducing the over-reliance on real human trials for assessing public policies? In this work, we investigate the feasibility of simulating health-related decision-making, using vaccine hesitancy, defined as the delay in acceptance ... | [
"Abe Bohan Hou",
"Hongru Du",
"Yichen Wang",
"Jingyu Zhang",
"Zixiao Wang",
"Paul Pu Liang",
"Daniel Khashabi",
"Lauren M Gardner",
"Tianxing He"
] | https://openreview.net/forum?id=zSbecER9il | zSbecER9il | zSbecER9il | [
"~Abe_Bohan_Hou1",
"~Hongru_Du1",
"~Yichen_Wang4",
"~Jingyu_Zhang2",
"~Zixiao_Wang6",
"~Paul_Pu_Liang1",
"~Daniel_Khashabi2",
"~Lauren_M_Gardner1",
"~Tianxing_He1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/efdbcf1c87e1f5c9d8ded3b5bd028477a557f88e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM agent",
"multi-agent system",
"social simulation",
"public health",
"AI for health"
] | 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{
hou2025can,
title={Can A Society of Generative Agents Simulate Human Behavior and Inform Public Health Policy? A Case Study on Vaccine Hesitancy},
author={Abe Bohan Hou and Hongru Du and Yichen Wang and Jingyu Zhang and Zixiao Wang and Paul Pu Liang and Daniel Khashabi and Lauren M Gardner and Tianxing ... | hou|can_a_society_of_generative_agents_simulate_human_behavior_and_inform_public_health_policy_a_case_study_on_vaccine_hesitancy | null | null | null | null | null | |
REFA: Reference Free Alignment with Fine-Grained Length Control | Reference-free alignment methods that optimize over multiple user preferences with fine-grained control of length | To mitigate reward hacking from response verbosity, modern preference optimization methods are increasingly adopting length normalization (e.g., SimPO, ORPO, LN-DPO). While effective against this bias, we demonstrate that length normalization itself introduces a failure mode: the **URSLA shortcut**. Here models learn t... | [
"Taneesh Gupta",
"Rahul Madhavan",
"Xuchao Zhang",
"Chetan Bansal",
"Saravan Rajmohan"
] | https://openreview.net/forum?id=zP6DJaBBcR | zP6DJaBBcR | zP6DJaBBcR | [
"~Taneesh_Gupta1",
"~Rahul_Madhavan1",
"~Xuchao_Zhang1",
"~Chetan_Bansal1",
"~Saravan_Rajmohan2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/dc1c639c05cb38e22dd2b44774293041d8886ec9.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Model Alignment",
"RLHF",
"Preference Optimization"
] | 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{
gupta2025refa,
title={{REFA}: Reference Free Alignment with Fine-Grained Length Control},
author={Taneesh Gupta and Rahul Madhavan and Xuchao Zhang and Chetan Bansal and Saravan Rajmohan},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=zP6DJaBBcR}
} | gupta|refa_reference_free_alignment_with_finegrained_length_control | null | null | null | null | null | |
Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution | We propose a fairness benchmark that evaluates intersectional biases in LLMs based on disparities in model confidence while performing coreference resolution on different intersectional identities | Large language models (LLMs) have achieved impressive performance, leading to their widespread adoption as decision-support tools in resource-constrained contexts like hiring and admissions. There is, however, scientific consensus that AI systems can reflect and exacerbate societal biases, raising concerns about identi... | [
"Falaah Arif Khan",
"Nivedha Sivakumar",
"Yinong Oliver Wang",
"Katherine Metcalf",
"Cezanne Camacho",
"Barry-John Theobald",
"Luca Zappella",
"Nicholas Apostoloff"
] | https://openreview.net/forum?id=zOw2it5Ni6 | zOw2it5Ni6 | zOw2it5Ni6 | [
"~Falaah_Arif_Khan1",
"~Nivedha_Sivakumar1",
"~Yinong_Oliver_Wang1",
"~Katherine_Metcalf1",
"~Cezanne_Camacho1",
"~Barry-John_Theobald1",
"~Luca_Zappella1",
"~Nicholas_Apostoloff1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/036165617f0c285d7a8f21490ec7432f50b68556.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"fairness",
"uncertainty",
"intersectionality"
] | 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{
khan2025investigating,
title={Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution},
author={Falaah Arif Khan and Nivedha Sivakumar and Yinong Oliver Wang and Katherine Metcalf and Cezanne Camacho and Barry-John Theobald and Luca Zappella and ... | khan|investigating_intersectional_bias_in_large_language_models_using_confidence_disparities_in_coreference_resolution | null | null | null | null | null | |
MeMAD: Structured Memory of Debates for Enhanced Multi-Agent Reasoning | We propose Memory-Augmented Multi-Agent Debate (MeMAD), which systematically organizes and reuses past debate transcripts to improve performance on complex reasoning tasks without requiring parameter updates. | Large Language Models (LLMs) demonstrate remarkable in-context learning capabilities but often struggle with complex, multi-step reasoning. Multi-Agent Debate (MAD) frameworks partially address these limitations by enabling iterative agent interactions. However, they neglect valuable historical insights by treating eac... | [
"Shuai Ling",
"Lizi Liao",
"Dongmei Jiang",
"Weili Guan"
] | https://openreview.net/forum?id=zLbmsdyTiN | zLbmsdyTiN | zLbmsdyTiN | [
"~Shuai_Ling1",
"~Lizi_Liao1",
"~Dongmei_Jiang2",
"~Weili_Guan4"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/a0b1930d621647e4dd73a698d9879287d9ebcb8d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Multi-Agent Debate",
"Memory Augmentation"
] | 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{
ling2025memad,
title={Me{MAD}: Structured Memory of Debates for Enhanced Multi-Agent Reasoning},
author={Shuai Ling and Lizi Liao and Dongmei Jiang and Weili Guan},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=zLbmsdyTiN}
} | ling|memad_structured_memory_of_debates_for_enhanced_multiagent_reasoning | null | null | null | null | null | |
Values in the Wild: Discovering and Mapping Values in Real-World Language Model Interactions | Our privacy-preserving analysis of values in real-world language model interactions reveals a novel taxonomy of AI values that differs from human frameworks, is highly context-dependent, and becomes most explicit/legible during moments of resistance. | AI assistants interact with millions of real users everyday, imparting normative judgments that can have significant personal and societal impact—but little is known about what values guide these interactions in practice. To address this, we develop a method to empirically analyze values expressed in hundreds of thousa... | [
"Saffron Huang",
"Esin DURMUS",
"Kunal Handa",
"Miles McCain",
"Alex Tamkin",
"Michael Stern",
"Jerry Hong",
"Deep Ganguli"
] | https://openreview.net/forum?id=zJHZJClG1Z | zJHZJClG1Z | zJHZJClG1Z | [
"~Saffron_Huang1",
"~Esin_DURMUS2",
"~Kunal_Handa1",
"~Miles_McCain1",
"~Alex_Tamkin1",
"~Michael_Stern1",
"~Jerry_Hong1",
"~Deep_Ganguli2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d9cb13b573fe0a00779ee4fba3d32dee93dce2d3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"language models",
"values",
"AI ethics",
"AI values",
"empirical analysis",
"human-AI interaction",
"value alignment",
"privacy-preserving analysis",
"value pluralism",
"AI and society"
] | 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{
huang2025values,
title={Values in the Wild: Discovering and Mapping Values in Real-World Language Model Interactions},
author={Saffron Huang and Esin DURMUS and Kunal Handa and Miles McCain and Alex Tamkin and Michael Stern and Jerry Hong and Deep Ganguli},
booktitle={Second Conference on Language Model... | huang|values_in_the_wild_discovering_and_mapping_values_in_realworld_language_model_interactions | null | null | null | null | null | |
Deep Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions | We propose a method to build virtual personas for deeper user binding and demonstrate its superiority in approximating metaperception in political science. | Large language models (LLMs) are increasingly capable of simulating human behavior, offering cost-effective ways to estimate user responses during the early phases of survey design. While previous studies have examined whether models can reflect individual opinions or attitudes, we argue that a higher-order binding of ... | [
"Minwoo Kang",
"Suhong Moon",
"Seung Hyeong Lee",
"Ayush Raj",
"Joseph Suh",
"David Chan"
] | https://openreview.net/forum?id=zHdSCtNmM4 | zHdSCtNmM4 | zHdSCtNmM4 | [
"~Minwoo_Kang1",
"~Suhong_Moon1",
"~Seung_Hyeong_Lee1",
"~Ayush_Raj3",
"~Joseph_Suh1",
"~David_Chan3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/08c4c62957f19503b9cb14a781f9366ed5d2ff58.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"user approximation",
"metaperception",
"social psycholog",
"democratic backsliding",
"outgroup hostility"
] | 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{
kang2025deep,
title={Deep Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions},
author={Minwoo Kang and Suhong Moon and Seung Hyeong Lee and Ayush Raj and Joseph Suh and David Chan},
booktitle={Second Conference on Language Modeling},
year={2025},
url={... | kang|deep_binding_of_language_model_virtual_personas_a_study_on_approximating_political_partisan_misperceptions | /attachment/887605a60f6440213636e72d74e01e35df30335b.zip | null | null | null | null | |
QUDsim: Quantifying Discourse Similarities in LLM-Generated Text | We introduce an abstraction based on linguistics theories in Questions Under Discussion (QUD) and question semantics to quantify repetitive discourse structures found in texts generated by large language models. | As large language models become increasingly capable at various tasks including writing, the need to generate unique and creative content arises. Although LLMs have the ability to generate text covering diverse topics, there is an overall sense of repetitiveness across texts that we aim to formalize. Such familiarity b... | [
"Ramya Namuduri",
"Yating Wu",
"Anshun Asher Zheng",
"Manya Wadhwa",
"Greg Durrett",
"Junyi Jessy Li"
] | https://openreview.net/forum?id=zFz1BJu211 | zFz1BJu211 | zFz1BJu211 | [
"~Ramya_Namuduri1",
"~Yating_Wu1",
"~Anshun_Asher_Zheng1",
"~Manya_Wadhwa1",
"~Greg_Durrett1",
"~Junyi_Jessy_Li2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5974197cbc65ce889f5cb6d2e8a8bf2a2394d65c.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"discourse diversity",
"discourse structure",
"large language models",
"Questions Under Discussion"
] | 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{
namuduri2025qudsim,
title={{QUD}sim: Quantifying Discourse Similarities in {LLM}-Generated Text},
author={Ramya Namuduri and Yating Wu and Anshun Asher Zheng and Manya Wadhwa and Greg Durrett and Junyi Jessy Li},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.ne... | namuduri|qudsim_quantifying_discourse_similarities_in_llmgenerated_text | null | null | null | null | null | |
Probing then Editing Response Personality of Large Language Models | This paper introduces a layer-wise probing framework revealing how LLMs encode personality traits within parameters and further proposes a progressive perturbation method that edits personality during inference using the probing classifier. | Large Language Models (LLMs) have demonstrated promising capabilities to generate responses that simulate consistent personality traits.
Despite the major attempts to analyze personality expression through output-based evaluations, little is known about how such traits are internally encoded within LLM parameters. In ... | [
"Tianjie Ju",
"Zhenyu Shao",
"Bowen Wang",
"Yujia Chen",
"Zhuosheng Zhang",
"Hao Fei",
"Mong-Li Lee",
"Wynne Hsu",
"Sufeng Duan",
"Gongshen Liu"
] | https://openreview.net/forum?id=z9SbcYYP0M | z9SbcYYP0M | z9SbcYYP0M | [
"~Tianjie_Ju1",
"~Zhenyu_Shao2",
"~Bowen_Wang10",
"~Yujia_Chen5",
"~Zhuosheng_Zhang1",
"~Hao_Fei1",
"~Mong-Li_Lee1",
"~Wynne_Hsu1",
"~Sufeng_Duan1",
"~Gongshen_Liu2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/498cc4dc5e0ee0f10ac6252c267617bc18a5cc09.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"large language model",
"personality",
"interpretability",
"knowledge editing"
] | 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{
ju2025probing,
title={Probing then Editing Response Personality of Large Language Models},
author={Tianjie Ju and Zhenyu Shao and Bowen Wang and Yujia Chen and Zhuosheng Zhang and Hao Fei and Mong-Li Lee and Wynne Hsu and Sufeng Duan and Gongshen Liu},
booktitle={Second Conference on Language Modeling},... | ju|probing_then_editing_response_personality_of_large_language_models | null | null | null | null | null | |
CodeXEmbed: A Generalist Embedding Model Family for Multilingual and Multi-task Code Retrieval | We introduce CodeXEmbed, a large-scale code embedding model achieving SOTA on CoIR and strong BeIR performance, enhancing code retrieval and RAG. | Despite the success of text retrieval in many NLP tasks, code retrieval remains a largely underexplored area. Most text retrieval systems are tailored for natural language queries, often neglecting the specific challenges of retrieving code. This gap leaves existing models unable to effectively capture the diversity of... | [
"Ye Liu",
"Rui Meng",
"Shafiq Joty",
"silvio savarese",
"Caiming Xiong",
"Yingbo Zhou",
"Semih Yavuz"
] | https://openreview.net/forum?id=z3lG70Azbg | z3lG70Azbg | z3lG70Azbg | [
"~Ye_Liu4",
"~Rui_Meng1",
"~Shafiq_Joty1",
"~silvio_savarese2",
"~Caiming_Xiong1",
"~Yingbo_Zhou1",
"~Semih_Yavuz1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/556d386c8c3457c2f182c786da442e3b3cbd673a.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Code and Text Retrieval; Code Embedding Model; Text Embedding Model; Retrieval-Augmented Code 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{
liu2025codexembed,
title={Code{XE}mbed: A Generalist Embedding Model Family for Multilingual and Multi-task Code Retrieval},
author={Ye Liu and Rui Meng and Shafiq Joty and silvio savarese and Caiming Xiong and Yingbo Zhou and Semih Yavuz},
booktitle={Second Conference on Language Modeling},
year={2025}... | liu|codexembed_a_generalist_embedding_model_family_for_multilingual_and_multitask_code_retrieval | null | null | null | null | null | |
Retrieval-Augmented Generation with Conflicting Evidence | We propose a benchmark and multi-agent framework for RAG systems to handle ambiguity, conflicting evidence, and misinformation in real-world retrieval scenarios. | Large language model (LLM) agents are increasingly employing retrieval-augmented generation (RAG) to improve the factuality of their responses. However, in practice, these systems often need to handle ambiguous user queries and potentially conflicting information from multiple sources while also suppressing inaccurate ... | [
"Han Wang",
"Archiki Prasad",
"Elias Stengel-Eskin",
"Mohit Bansal"
] | https://openreview.net/forum?id=z1MHB2m3V9 | z1MHB2m3V9 | z1MHB2m3V9 | [
"~Han_Wang9",
"~Archiki_Prasad1",
"~Elias_Stengel-Eskin1",
"~Mohit_Bansal2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/1452223fd8e091c35c8990c14f2d5e4979e749bc.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Retrieval-augmented Generation",
"Knowledge Conflict",
"Multi-agent"
] | 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{
wang2025retrievalaugmented,
title={Retrieval-Augmented Generation with Conflicting Evidence},
author={Han Wang and Archiki Prasad and Elias Stengel-Eskin and Mohit Bansal},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=z1MHB2m3V9}
} | wang|retrievalaugmented_generation_with_conflicting_evidence | null | null | null | null | null | |
Déjà Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation | What can multilingual LLM evaluation learn from MT evaluation? | Generation capabilities and language coverage of multilingual large language models (mLLMs) are advancing rapidly. However, evaluation practices for generative abilities of mLLMs are still lacking comprehensiveness, scientific rigor, and consistent adoption across research labs, which undermines their potential to mean... | [
"Julia Kreutzer",
"Eleftheria Briakou",
"Sweta Agrawal",
"Marzieh Fadaee",
"Tom Kocmi"
] | https://openreview.net/forum?id=yxzVanFoij | yxzVanFoij | yxzVanFoij | [
"~Julia_Kreutzer1",
"~Eleftheria_Briakou1",
"~Sweta_Agrawal1",
"~Marzieh_Fadaee2",
"~Tom_Kocmi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d390b099c4e0bc139be3a1a975837803ed0bf6db.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"multilingual",
"evaluation",
"meta-evaluation",
"machine translation 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{
kreutzer2025dj,
title={D\'ej\`a Vu: Multilingual {LLM} Evaluation through the Lens of Machine Translation Evaluation},
author={Julia Kreutzer and Eleftheria Briakou and Sweta Agrawal and Marzieh Fadaee and Tom Kocmi},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openrevi... | kreutzer|déjà_vu_multilingual_llm_evaluation_through_the_lens_of_machine_translation_evaluation | null | null | null | null | null | |
CONCAP: Seeing Beyond English with Concepts Retrieval-Augmented Captioning | Image captioning with concept and captions retrieval augmented generation. | Multilingual vision-language models have made significant strides in image captioning, yet they still lag behind their English counterparts due to limited multilingual training data and costly large-scale model parameterization. Retrieval-augmented generation (RAG) offers a promising alternative by conditioning caption... | [
"George Ibrahim",
"Rita Ramos",
"Yova Kementchedjhieva"
] | https://openreview.net/forum?id=yfnaK1pZxu | yfnaK1pZxu | yfnaK1pZxu | [
"~George_Ibrahim1",
"~Rita_Ramos1",
"~Yova_Kementchedjhieva1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/b261ae04f4cd4225e18480084dc5543014d43819.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Image Captioning",
"Concepts",
"Retrieval",
"RAG",
"Multilingual"
] | 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{
ibrahim2025concap,
title={{CONCAP}: Seeing Beyond English with Concepts Retrieval-Augmented Captioning},
author={George Ibrahim and Rita Ramos and Yova Kementchedjhieva},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=yfnaK1pZxu}
} | ibrahim|concap_seeing_beyond_english_with_concepts_retrievalaugmented_captioning | null | null | null | null | null | |
Prompt-Reverse Inconsistency: LLM Self-Inconsistency Beyond Generative Randomness and Prompt Paraphrasing | This paper introduces Prompt-Reverse Inconsistency (PRIN), where Large Language Models give conflicting answers when identifying correct versus incorrect responses, raising concerns about their logical reliability. | While the inconsistency of LLMs is not a novel topic, prior research has predominantly addressed two types of generative inconsistencies: i) Randomness Inconsistency: running the same LLM multiple trials, yielding varying responses; ii) Paraphrase Inconsistency: paraphrased prompts result in different responses from th... | [
"Jihyun Janice Ahn",
"Wenpeng Yin"
] | https://openreview.net/forum?id=yfRkNRFLzl | yfRkNRFLzl | yfRkNRFLzl | [
"~Jihyun_Janice_Ahn1",
"~Wenpeng_Yin1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/44b6a89c82f5042a567ea17d3070285af52ead04.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Model",
"Natural Language Process",
"Inconsistency of LLMs",
"Prompt-Reverse Inconsistency",
"Randomness Inconsistency",
"Paraphrase Inconsistency"
] | 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{
ahn2025promptreverse,
title={Prompt-Reverse Inconsistency: {LLM} Self-Inconsistency Beyond Generative Randomness and Prompt Paraphrasing},
author={Jihyun Janice Ahn and Wenpeng Yin},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=yfRkNRFLzl}
} | ahn|promptreverse_inconsistency_llm_selfinconsistency_beyond_generative_randomness_and_prompt_paraphrasing | null | null | null | null | null | |
Learning to Generate Unit Tests for Automated Debugging | LLM training pipeline for generating unit tests for code debugging and assessing code correctness | Unit tests (UTs) play an instrumental role in assessing code correctness as well as providing feedback to large language models (LLMs), motivating automated test generation. However, we uncover a trade-off between generating unit test inputs that reveal errors when given a faulty code and correctly predicting the unit ... | [
"Archiki Prasad",
"Elias Stengel-Eskin",
"Justin Chen",
"Zaid Khan",
"Mohit Bansal"
] | https://openreview.net/forum?id=yeVBHPLXxi | yeVBHPLXxi | yeVBHPLXxi | [
"~Archiki_Prasad1",
"~Elias_Stengel-Eskin1",
"~Justin_Chen1",
"~Zaid_Khan1",
"~Mohit_Bansal2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d0e3dc4e72f75d7f7f18fe8c0ab78512b18f88a0.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Unit Tests Generation",
"LLMs for code generation",
"LLMs for code debugging"
] | 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{
prasad2025learning,
title={Learning to Generate Unit Tests for Automated Debugging},
author={Archiki Prasad and Elias Stengel-Eskin and Justin Chen and Zaid Khan and Mohit Bansal},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=yeVBHPLXxi}
} | prasad|learning_to_generate_unit_tests_for_automated_debugging | /attachment/f3e3abd874e6c1ad0a461bbcbb6c9cf7fe922262.zip | null | null | null | null | |
VideoSAVi: Self-Aligned Video Language Models without Human Supervision | VideoSAVi introduces a self-aligning approach that enables video-language models to generate high-quality preference pairs from their own outputs, achieving state-of-the-art performance without external supervision. | Recent advances in video-large language models (Video-LLMs) have led to significant progress in video understanding. Current preference optimization methods often rely on proprietary APIs or ground-truth captions to generate preference data (i.e., pairs of model outputs ranked based on their quality or alignment with h... | [
"Yogesh Kulkarni",
"Pooyan Fazli"
] | https://openreview.net/forum?id=ybcZEWaM7U | ybcZEWaM7U | ybcZEWaM7U | [
"~Yogesh_Kulkarni1",
"~Pooyan_Fazli1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5846d0a6f494f556df2f25ba346da586faf3d28b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Video understanding",
"Self-alignment",
"Video-language models",
"Direct preference optimization",
"Self-critiquing"
] | 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{
kulkarni2025videosavi,
title={Video{SAV}i: Self-Aligned Video Language Models without Human Supervision},
author={Yogesh Kulkarni and Pooyan Fazli},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=ybcZEWaM7U}
} | kulkarni|videosavi_selfaligned_video_language_models_without_human_supervision | null | null | null | null | null | |
Streaming DiLoCo with overlapping communication | Distributed training where only a subset of the outer gradients is communicated | Training of large language models (LLMs) is typically distributed across a large number of accelerators to reduce training time. Since internal states and parameter gradients need to be exchanged at each and every single gradient step, all devices need to be co-located using low-latency high-bandwidth communication lin... | [
"Arthur Douillard",
"Yani Donchev",
"J Keith Rush",
"Satyen Kale",
"Zachary Charles",
"Gabriel Teston",
"Zachary Garrett",
"Jiajun Shen",
"Ross McIlroy",
"David Lacey",
"Alexandre Rame",
"Arthur Szlam",
"MarcAurelio Ranzato",
"Paul R Barham"
] | https://openreview.net/forum?id=yYk3zK0X6Q | yYk3zK0X6Q | yYk3zK0X6Q | [
"~Arthur_Douillard1",
"~Yani_Donchev1",
"~J_Keith_Rush1",
"~Satyen_Kale2",
"~Zachary_Charles1",
"~Gabriel_Teston1",
"~Zachary_Garrett1",
"~Jiajun_Shen1",
"~Ross_McIlroy1",
"~David_Lacey1",
"~Alexandre_Rame1",
"~Arthur_Szlam3",
"~MarcAurelio_Ranzato1",
"~Paul_R_Barham2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/cfdba2f22f8184c00ce2bee496c5685b22b6922e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"distributed training",
"large-scale",
"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{
douillard2025streaming,
title={Streaming DiLoCo with overlapping communication},
author={Arthur Douillard and Yani Donchev and J Keith Rush and Satyen Kale and Zachary Charles and Gabriel Teston and Zachary Garrett and Jiajun Shen and Ross McIlroy and David Lacey and Alexandre Rame and Arthur Szlam and ... | douillard|streaming_diloco_with_overlapping_communication | null | null | null | null | null | |
Multilingual and Multi-Accent Jailbreaking of Audio LLMs | We propose Multi-AudioJail --- a novel audio jailbreak attack that exploits multilingual and multi-accent audio inputs enhanced with audio adversarial perturbations. | Large Audio Language Models (LALMs) have significantly advanced audio understanding but introduce critical security risks, particularly through audio jailbreaks. While prior work has focused on English-centric attacks, we expose a far more severe vulnerability: adversarial multilingual and multi-accent audio jailbreaks... | [
"Jaechul Roh",
"Virat Shejwalkar",
"Amir Houmansadr"
] | https://openreview.net/forum?id=yGa8CYT8kS | yGa8CYT8kS | yGa8CYT8kS | [
"~Jaechul_Roh1",
"~Virat_Shejwalkar1",
"~Amir_Houmansadr1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/6147a6961d7ae656a86a7d1238824560951dada6.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Audio",
"LLM",
"Jailbreak",
"Multilingual",
"Security"
] | 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 | the audio jailbreaking might be offensive to some audience.
| @inproceedings{
roh2025multilingual,
title={Multilingual and Multi-Accent Jailbreaking of Audio {LLM}s},
author={Jaechul Roh and Virat Shejwalkar and Amir Houmansadr},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=yGa8CYT8kS}
} | roh|multilingual_and_multiaccent_jailbreaking_of_audio_llms | null | null | null | null | null | |
Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models | We introduce a novel inference-time algorithm, ThoughtTracing, which uses LLMs to probabilistically trace and weight hypotheses about agents’ evolving mental states without relying on questions and ground-truth answers in benchmarks. | Existing LLM reasoning methods have shown impressive capabilities across various tasks, such as solving math and coding problems. However, applying these methods to scenarios without ground-truth answers or rule-based verification methods - such as tracking the mental states of an agent - remains challenging. Inspired ... | [
"Hyunwoo Kim",
"Melanie Sclar",
"Tan Zhi-Xuan",
"Lance Ying",
"Sydney Levine",
"Yang Liu",
"Joshua B. Tenenbaum",
"Yejin Choi"
] | https://openreview.net/forum?id=yGQqTuSJPK | yGQqTuSJPK | yGQqTuSJPK | [
"~Hyunwoo_Kim3",
"~Melanie_Sclar1",
"~Tan_Zhi-Xuan1",
"~Lance_Ying1",
"~Sydney_Levine1",
"~Yang_Liu60",
"~Joshua_B._Tenenbaum1",
"~Yejin_Choi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5d8ab1d8f4c22c924ea0d6ee9ae0a18ef00a958b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"theory of mind",
"reasoning",
"large language model",
"inference-time algorithm"
] | 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{
kim2025hypothesisdriven,
title={Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models},
author={Hyunwoo Kim and Melanie Sclar and Tan Zhi-Xuan and Lance Ying and Sydney Levine and Yang Liu and Joshua B. Tenenbaum and Yejin Choi},
booktitle={Second Conference on Language Modeling},
year={2... | kim|hypothesisdriven_theoryofmind_reasoning_for_large_language_models | null | null | null | null | null | |
IterKey: Iterative Keyword Generation with LLMs for Enhanced Retrieval Augmented Generation | We introduce IterKey, an LLM-based iterative keyword generation method that optimize the Retrieval-Augmented Generation process, improving accuracy by refining keywords and self-evaluating responses. | Retrieval Augmented Generation (RAG) has emerged as a way to complement the in-context knowledge of Large Language Models (LLMs) by integrating external documents.
However, real-world applications demand not only accuracy but also interpretability.
Dense retrieval methods provide high accuracy but lack interpretabili... | [
"Kazuki Hayashi",
"Hidetaka Kamigaito",
"Shinya Kouda",
"Taro Watanabe"
] | https://openreview.net/forum?id=y56BuSo8Uj | y56BuSo8Uj | y56BuSo8Uj | [
"~Kazuki_Hayashi1",
"~Hidetaka_Kamigaito2",
"~Shinya_Kouda1",
"~Taro_Watanabe1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/89b81fc6b363dd0e2529ebd9dbc0474cdee121a7.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"retrieval-augmented generation",
"RAG",
"sparse retrieval",
"LLM",
"Iterative"
] | 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{
hayashi2025iterkey,
title={IterKey: Iterative Keyword Generation with {LLM}s for Enhanced Retrieval Augmented Generation},
author={Kazuki Hayashi and Hidetaka Kamigaito and Shinya Kouda and Taro Watanabe},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum... | hayashi|iterkey_iterative_keyword_generation_with_llms_for_enhanced_retrieval_augmented_generation | null | null | null | null | null | |
Can LLM "Self-report"?: Evaluating the Validity of Self-report Scales in Measuring Personality Design in LLM-based Chatbots | Evaluating the Validity of Self-report Scales in Measuring Personality Design in LLM-based Chatbots | A chatbot’s personality design is key to interaction quality. As chatbots evolved from rule-based systems to those powered by large language models (LLMs), evaluating the effectiveness of their personality design has become increasingly complex, particularly due to the open-ended nature of interactions. A recent and wi... | [
"Huiqi Zou",
"Pengda Wang",
"Zihan Yan",
"Tianjun Sun",
"Ziang Xiao"
] | https://openreview.net/forum?id=xqIwK9mNkj | xqIwK9mNkj | xqIwK9mNkj | [
"~Huiqi_Zou1",
"~Pengda_Wang1",
"~Zihan_Yan1",
"~Tianjun_Sun1",
"~Ziang_Xiao1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/388bb244be1dd675a49c4295cc3cd296fe6906a1.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"human factors in NLP; evaluation methodologies"
] | 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{
zou2025can,
title={Can {LLM} ''Self-report''?: Evaluating the Validity of Self-report Scales in Measuring Personality Design in {LLM}-based Chatbots},
author={Huiqi Zou and Pengda Wang and Zihan Yan and Tianjun Sun and Ziang Xiao},
booktitle={Second Conference on Language Modeling},
year={2025},
url={ht... | zou|can_llm_selfreport_evaluating_the_validity_of_selfreport_scales_in_measuring_personality_design_in_llmbased_chatbots | null | null | null | null | null | |
Always Tell Me The Odds: Fine-grained Conditional Probability Estimation | We present a state-of-the-art model for fine-grained probability estimation of textual outcomes conditioned on context. | We present a state-of-the-art model for fine-grained probability estimation of propositions conditioned on context. Recent advances in large language models (LLMs) have significantly enhanced their reasoning capabilities, particularly on well-defined tasks with complete information. However, LLMs continue to struggle w... | [
"Liaoyaqi Wang",
"Zhengping Jiang",
"Anqi Liu",
"Benjamin Van Durme"
] | https://openreview.net/forum?id=xhDcG8qtw9 | xhDcG8qtw9 | xhDcG8qtw9 | [
"~Liaoyaqi_Wang1",
"~Zhengping_Jiang1",
"~Anqi_Liu2",
"~Benjamin_Van_Durme2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c53d10b668e237deedcef8b115cc9a506df677e2.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Model",
"Probabilistic Reasoning",
"Semantics",
"Calibration"
] | 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{
wang2025always,
title={Always Tell Me The Odds: Fine-grained Conditional Probability Estimation},
author={Liaoyaqi Wang and Zhengping Jiang and Anqi Liu and Benjamin Van Durme},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=xhDcG8qtw9}
} | wang|always_tell_me_the_odds_finegrained_conditional_probability_estimation | null | null | null | null | null | |
CALLME: Call Graph Augmentation with Large Language Models for Javascript | Handling edge cases in call graph construction for Javascript that cannot be handled with static analysis using large language models. | Building precise call graphs for Javascript programs is a fundamental build-
ing block for many important software engineering and security applications
such as bug detection, program repair, and refactoring. However, resolving
dynamic calls using static analysis is challenging because it requires
enumerating all possi... | [
"Michael Wang",
"Kexin Pei",
"Armando Solar-Lezama"
] | https://openreview.net/forum?id=xZi2rMUcAO | xZi2rMUcAO | xZi2rMUcAO | [
"~Michael_Wang1",
"~Kexin_Pei1",
"~Armando_Solar-Lezama1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/41f82f781ab3f27465ee5b45ef2e3218c13a0f63.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Javascript",
"program analysis"
] | 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{
wang2025callme,
title={{CALLME}: Call Graph Augmentation with Large Language Models for Javascript},
author={Michael Wang and Kexin Pei and Armando Solar-Lezama},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=xZi2rMUcAO}
} | wang|callme_call_graph_augmentation_with_large_language_models_for_javascript | null | null | null | null | null | |
Adaptive Computation Pruning for the Forgetting Transformer | We propose a method that adaptively prunes computations in the Forgetting Transformer based on forget gate values. | The recently proposed Forgetting Transformer (FoX) incorporates a forget gate into softmax attention and has shown consistently better or on-par performance compared to the standard RoPE-based Transformer. Notably, many attention heads in FoX tend to forget quickly, causing their output at each timestep to rely primari... | [
"Zhixuan Lin",
"Johan Obando-Ceron",
"Xu Owen He",
"Aaron Courville"
] | https://openreview.net/forum?id=xNj14CY5S1 | xNj14CY5S1 | xNj14CY5S1 | [
"~Zhixuan_Lin1",
"~Johan_Obando-Ceron1",
"~Xu_Owen_He1",
"~Aaron_Courville3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/dabdb7eb3af1dbd15e1d91d6bb30f2a59bd77334.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"transformer",
"forgetting transformer",
"efficient transformer",
"sequence modeling",
"adaptive computation pruning",
"forget gate",
"sparse attention",
"FlashAttention",
"hardware-aware optimization"
] | 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{
lin2025adaptive,
title={Adaptive Computation Pruning for the Forgetting Transformer},
author={Zhixuan Lin and Johan Obando-Ceron and Xu Owen He and Aaron Courville},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=xNj14CY5S1}
} | lin|adaptive_computation_pruning_for_the_forgetting_transformer | null | null | null | null | null | |
Energy-Based Reward Models for Robust Language Model Alignment | We introduce Energy-Based Reward Model (EBRM), a post-hoc method to refine reward models using EBMs. | Reward models (RMs) are essential for aligning Large Language Models (LLMs) with human preference. However, they often struggle with capturing complex human preferences and generalizing to unseen data. To address these challenges, we introduce \emph{Energy-Based Reward Model} (EBRM), a lightweight post-hoc refinement f... | [
"Anamika Lochab",
"Ruqi Zhang"
] | https://openreview.net/forum?id=x6evCULIOQ | x6evCULIOQ | x6evCULIOQ | [
"~Anamika_Lochab1",
"~Ruqi_Zhang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/0cbcf905a030463b01e16ef7de935a5d0ef38517.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Reward Models",
"Alignment",
"Energy Based 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{
lochab2025energybased,
title={Energy-Based Reward Models for Robust Language Model Alignment},
author={Anamika Lochab and Ruqi Zhang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=x6evCULIOQ}
} | lochab|energybased_reward_models_for_robust_language_model_alignment | /attachment/d94995fd2c118eb604ec15b3b03867d739a2ce0c.zip | null | null | null | null | |
Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees | We propose a reasoning pipeline for penetration testing LLM agents using a structured task tree based on proven cybersecurity kill chains. Our method achieves 74.4% attack subtask completion (vs. 35.2% by the SOTA) and requires 55.9% fewer queries. | Recent advances in large language models (LLMs) have driven interest in automating cybersecurity penetration testing workflows, offering the promise of faster and more consistent vulnerability assessment for enterprise systems. Existing LLM agents for penetration testing primarily rely on self‐guided reasoning, which c... | [
"Katsuaki Nakano",
"Reza Fayyazi",
"Shanchieh Yang",
"Michael Zuzak"
] | https://openreview.net/forum?id=x4sdXZ7Jdu | x4sdXZ7Jdu | x4sdXZ7Jdu | [
"~Katsuaki_Nakano1",
"~Reza_Fayyazi1",
"~Shanchieh_Yang1",
"~Michael_Zuzak1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/972da2fcf7e33064c89c2aed8f19ab736d656ab1.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Penetration Testing",
"Large Language Models",
"Autonomous Penetration Testing 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{
nakano2025guided,
title={Guided Reasoning in {LLM}-Driven Penetration Testing Using Structured Attack Trees},
author={Katsuaki Nakano and Reza Fayyazi and Shanchieh Yang and Michael Zuzak},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=x4sdXZ7Jdu}
... | nakano|guided_reasoning_in_llmdriven_penetration_testing_using_structured_attack_trees | null | null | null | null | null | |
Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving | Introduce Goedel-Prover, an open-source language model that achieves SOTA in automated theorem proving in Lean | We introduce Goedel-Prover, an open-source language model that achieves state-of-the-art performance in automated formal proof generation for mathematical problems. A key challenge in this field is the scarcity of formalized mathematical statements and proofs, which we address through the following approaches. First, ... | [
"Yong Lin",
"Shange Tang",
"Bohan Lyu",
"Jiayun Wu",
"Hongzhou Lin",
"Kaiyu Yang",
"Jia LI",
"Mengzhou Xia",
"Danqi Chen",
"Sanjeev Arora",
"Chi Jin"
] | https://openreview.net/forum?id=x2y9i2HDjD | x2y9i2HDjD | x2y9i2HDjD | [
"~Yong_Lin2",
"~Shange_Tang1",
"~Bohan_Lyu1",
"~Jiayun_Wu1",
"~Hongzhou_Lin1",
"~Kaiyu_Yang1",
"~Jia_LI18",
"~Mengzhou_Xia1",
"~Danqi_Chen1",
"~Sanjeev_Arora1",
"~Chi_Jin1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/047be6bba4d4ce1c4aae8dfe2c987deef335ef45.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Formal reasoning",
"verification",
"Lean",
"self-improvement"
] | 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{
lin2025goedelprover,
title={Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving},
author={Yong Lin and Shange Tang and Bohan Lyu and Jiayun Wu and Hongzhou Lin and Kaiyu Yang and Jia LI and Mengzhou Xia and Danqi Chen and Sanjeev Arora and Chi Jin},
booktitle={Second Conference on ... | lin|goedelprover_a_frontier_model_for_opensource_automated_theorem_proving | null | null | null | null | null | |
EnrichIndex: Using LLMs to Enrich Retrieval Indices Offline | EnrichIndex enriches documents offline using LLMs, improving retrieval performance on complex retrieval tasks with significantly lower latency and online cost. | Existing information retrieval systems excel in cases where the language of target documents closely matches that of the user query. However, real-world retrieval systems are often required to *implicitly reason* whether a document is relevant. For example, when retrieving technical texts or tables, their relevance to ... | [
"Peter Baile Chen",
"Tomer Wolfson",
"Mike Cafarella",
"Dan Roth"
] | https://openreview.net/forum?id=wyYL5Jov6e | wyYL5Jov6e | wyYL5Jov6e | [
"~Peter_Baile_Chen1",
"~Tomer_Wolfson1",
"~Mike_Cafarella1",
"~Dan_Roth3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/7e22d77624c4e6b84c79cf58406e46c07740df64.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"retrieval",
"offline enrichment",
"implicit 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{
chen2025enrichindex,
title={EnrichIndex: Using {LLM}s to Enrich Retrieval Indices Offline},
author={Peter Baile Chen and Tomer Wolfson and Mike Cafarella and Dan Roth},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=wyYL5Jov6e}
} | chen|enrichindex_using_llms_to_enrich_retrieval_indices_offline | null | null | null | null | null | |
Elucidating the Design Space of Decay in Linear Attention | Elucidating the Design Space of Decay in Linear Attention | This paper presents a comprehensive investigation into the decay mechanisms inherent in linear complexity sequence models. We systematically delineate the design space of decay mechanisms across four pivotal dimensions: parameterization strategy, which refers to the computational methodology for decay; parameter sharin... | [
"Zhen Qin",
"Xuyang Shen",
"Yiran Zhong"
] | https://openreview.net/forum?id=whXh2YxMbt | whXh2YxMbt | whXh2YxMbt | [
"~Zhen_Qin6",
"~Xuyang_Shen1",
"~Yiran_Zhong1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/815a0f2594e2d32ff855a8a9d677e3855205a1c4.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Linear 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{
qin2025elucidating,
title={Elucidating the Design Space of Decay in Linear Attention},
author={Zhen Qin and Xuyang Shen and Yiran Zhong},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=whXh2YxMbt}
} | qin|elucidating_the_design_space_of_decay_in_linear_attention | null | null | null | null | null | |
PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages | We introduce PolyGuard, a new state-of-the-art multilingual safety model for safeguarding LLM generations along with PolyGuardMix for safety detection training and PolyGuardPrompts for safety guardrail evaluation. | Truly multilingual safety moderation efforts for Large Language Models (LLMs) have been hindered by a narrow focus on a small set of languages (e.g., English, Chinese) as well as a limited scope of safety definition, resulting in significant gaps in moderation capabilities. To bridge these gaps, we release POLYGUARD, a... | [
"Priyanshu Kumar",
"Devansh Jain",
"Akhila Yerukola",
"Liwei Jiang",
"Himanshu Beniwal",
"Thomas Hartvigsen",
"Maarten Sap"
] | https://openreview.net/forum?id=wbAWKXNeQ4 | wbAWKXNeQ4 | wbAWKXNeQ4 | [
"~Priyanshu_Kumar1",
"~Devansh_Jain1",
"~Akhila_Yerukola1",
"~Liwei_Jiang2",
"~Himanshu_Beniwal1",
"~Thomas_Hartvigsen1",
"~Maarten_Sap1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/083b5e10f049e428ff125b8665aea78cf0284e75.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"ai safety",
"hate-speech detection"
] | 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{
kumar2025polyguard,
title={PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages},
author={Priyanshu Kumar and Devansh Jain and Akhila Yerukola and Liwei Jiang and Himanshu Beniwal and Thomas Hartvigsen and Maarten Sap},
booktitle={Second Conference on Language Modeling},
year={2025},
url={h... | kumar|polyguard_a_multilingual_safety_moderation_tool_for_17_languages | null | null | null | null | null | |
More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in DPO Safety Alignment | LLMs learns about safety better from their own outputs than from others. | Aligning large language models (LLMs) with human values is an increasingly critical step in post-training. Direct Preference Optimization (DPO) has emerged as a simple, yet effective alternative to reinforcement learning from human feedback (RLHF). Synthetic preference data with its low cost and high quality enable eff... | [
"Yifan Wang",
"Runjin Chen",
"Bolian Li",
"David Cho",
"Yihe Deng",
"Ruqi Zhang",
"Tianlong Chen",
"Zhangyang Wang",
"Ananth Grama",
"Junyuan Hong"
] | https://openreview.net/forum?id=wXOUYzNv5k | wXOUYzNv5k | wXOUYzNv5k | [
"~Yifan_Wang14",
"~Runjin_Chen1",
"~Bolian_Li1",
"~David_Cho2",
"~Yihe_Deng1",
"~Ruqi_Zhang1",
"~Tianlong_Chen1",
"~Zhangyang_Wang1",
"~Ananth_Grama1",
"~Junyuan_Hong1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/094c4e24c1d72adc8f0ceeded062c9fdf6235d7b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Alignment",
"Synthetic Data",
"Safety",
"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{
wang2025more,
title={More is Less: The Pitfalls of Multi-Model Synthetic Preference Data in {DPO} Safety Alignment},
author={Yifan Wang and Runjin Chen and Bolian Li and David Cho and Yihe Deng and Ruqi Zhang and Tianlong Chen and Zhangyang Wang and Ananth Grama and Junyuan Hong},
booktitle={Second Conf... | wang|more_is_less_the_pitfalls_of_multimodel_synthetic_preference_data_in_dpo_safety_alignment | null | null | null | null | null | |
Sherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Setting | Sherkala-Chat (8B) is a state-of-the-art, instruction-tuned open LLM for Kazakh, excelling in Kazakh language tasks while remaining competitive in English. | Llama-3.1-Sherkala-8B-Chat, or Sherkala-Chat (8B) for short, is a state-of-the-art instruction-tuned open generative large language model (LLM) designed for Kazakh. Sherkala-Chat (8B) aims to enhance the inclusivity of LLM advancements for Kazakh speakers. Adapted from the LLaMA-3.1-8B model, Sherkala-Chat (8B) is trai... | [
"Fajri Koto",
"Rituraj Joshi",
"Nurdaulet Mukhituly",
"Yuxia Wang",
"Zhuohan Xie",
"Rahul Pal",
"Daniil Orel",
"Parvez Mullah",
"Diana Turmakhan",
"Maiya Goloburda",
"Mohammed Kamran",
"Samujjwal Ghosh",
"Bokang Jia",
"Jonibek Mansurov",
"Mukhammed Togmanov",
"Debopriyo Banerjee",
"N... | https://openreview.net/forum?id=wRcTCcb0H5 | wRcTCcb0H5 | wRcTCcb0H5 | [
"~Fajri_Koto1",
"~Rituraj_Joshi1",
"~Nurdaulet_Mukhituly1",
"~Yuxia_Wang1",
"~Zhuohan_Xie1",
"~Rahul_Pal1",
"~Daniil_Orel1",
"~Parvez_Mullah1",
"~Diana_Turmakhan1",
"~Maiya_Goloburda1",
"~Mohammed_Kamran1",
"~Samujjwal_Ghosh1",
"~Bokang_Jia1",
"~Jonibek_Mansurov1",
"~Mukhammed_Togmanov1"... | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/81303233cce33f5509d80aa0ef16ce80cdba0fb8.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM",
"LLaMA-3.1",
"Kazakh",
"low-resource language modeling",
"fine-tuning",
"safety alignment",
"model evaluation",
"generative AI"
] | 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{
koto2025sherkalachat,
title={Sherkala-Chat: Building a State-of-the-Art {LLM} for Kazakh in a Moderately Resourced Setting},
author={Fajri Koto and Rituraj Joshi and Nurdaulet Mukhituly and Yuxia Wang and Zhuohan Xie and Rahul Pal and Daniil Orel and Parvez Mullah and Diana Turmakhan and Maiya Goloburda... | koto|sherkalachat_building_a_stateoftheart_llm_for_kazakh_in_a_moderately_resourced_setting | null | null | null | null | null | |
Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective | We introduce a framework for assessing and analyzing bias in long text outputs at group level. | Large Language Models (LLMs) often generate responses with inherent biases,
undermining their reliability in real-world applications. Existing evaluation meth-
ods often overlook biases in long-form responses and the intrinsic variability of
LLM outputs. To address these challenges, we propose FiSCo (Fine-grained Se-
m... | [
"Weijie Xu",
"Yiwen Wang",
"Chi Xue",
"Xiangkun Hu",
"Xi Fang",
"Guimin Dong",
"Chandan K. Reddy"
] | https://openreview.net/forum?id=wKVtjs0w4a | wKVtjs0w4a | wKVtjs0w4a | [
"~Weijie_Xu1",
"~Yiwen_Wang4",
"~Chi_Xue1",
"~Xiangkun_Hu1",
"~Xi_Fang3",
"~Guimin_Dong1",
"~Chandan_K._Reddy1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/371c9407949422ef1df4a9f9b27d0ad0aa911a2b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Fairness",
"Bias",
"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{
xu2025quantifying,
title={Quantifying Fairness in {LLM}s Beyond Tokens: A Semantic and Statistical Perspective},
author={Weijie Xu and Yiwen Wang and Chi Xue and Xiangkun Hu and Xi Fang and Guimin Dong and Chandan K. Reddy},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://o... | xu|quantifying_fairness_in_llms_beyond_tokens_a_semantic_and_statistical_perspective | null | null | null | null | null | |
How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence | We compare base(pretrained) LLM and instruct(post-trained) LLM mechanistically in four perspectives and provide insight to what is preserved and altered. | Post-training is essential for the success of large language models (LLMs), transforming pre-trained base models into more useful and aligned post-trained models. While plenty of works have studied post-training algorithms and evaluated post-training models by their outputs, it remains understudied how post-training re... | [
"Hongzhe Du",
"Weikai Li",
"Min Cai",
"Karim Saraipour",
"Zimin Zhang",
"Himabindu Lakkaraju",
"Yizhou Sun",
"Shichang Zhang"
] | https://openreview.net/forum?id=w5DSwn9wTC | w5DSwn9wTC | w5DSwn9wTC | [
"~Hongzhe_Du1",
"~Weikai_Li2",
"~Min_Cai2",
"~Karim_Saraipour1",
"~Zimin_Zhang1",
"~Himabindu_Lakkaraju1",
"~Yizhou_Sun1",
"~Shichang_Zhang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ed7d9a75939697cf5c03dbd93501fd32e855ede6.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Mechanistic Interpretability",
"Instruction-tuning",
"Post-training",
"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{
du2025how,
title={How Post-Training Reshapes {LLM}s: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence},
author={Hongzhe Du and Weikai Li and Min Cai and Karim Saraipour and Zimin Zhang and Himabindu Lakkaraju and Yizhou Sun and Shichang Zhang},
booktitle={Second Conference on Langu... | du|how_posttraining_reshapes_llms_a_mechanistic_view_on_knowledge_truthfulness_refusal_and_confidence | null | null | null | null | null | |
The Zero Body Problem: Probing LLM Use of Sensory Language | Popular large language models fail to replicate human use of sensory language, an important feature of storytelling. | Sensory language expresses embodied experiences ranging from taste and sound to excitement and stomachache. It is of interest to scholars from a wide range of domains including robotics, narratology, linguistics, and cognitive science. In this work, we explore whether language models, which are not embodied, can approx... | [
"Rebecca M. M. Hicke",
"Sil Hamilton",
"David Mimno"
] | https://openreview.net/forum?id=vv1ZyQF8LD | vv1ZyQF8LD | vv1ZyQF8LD | [
"~Rebecca_M._M._Hicke1",
"~Sil_Hamilton1",
"~David_Mimno1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/3c070894fc335f646c5bbdc34c6ec387206d6861.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"model evaluation",
"model interpretability",
"sensory language",
"model creativity"
] | 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{
hicke2025the,
title={The Zero Body Problem: Probing {LLM} Use of Sensory Language},
author={Rebecca M. M. Hicke and Sil Hamilton and David Mimno},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=vv1ZyQF8LD}
} | hicke|the_zero_body_problem_probing_llm_use_of_sensory_language | null | null | null | null | null | |
Base Models Beat Aligned Models at Randomness and Creativity | Alignment seems to hurt performance on a set of tasks that require randomness or creativity | Alignment has quickly become a default ingredient in LLM development, with techniques such as reinforcement learning from human feedback making models act safely, follow instructions, and perform ever-better on complex tasks. While these techniques are certainly useful, we propose that they should not be universally ap... | [
"Peter West",
"Christopher Potts"
] | https://openreview.net/forum?id=vqN8uom4A1 | vqN8uom4A1 | vqN8uom4A1 | [
"~Peter_West1",
"~Christopher_Potts1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/fac784fe4c8e095a2a44374be0e7e9378dc7c012.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"alignment",
"pretrained",
"limitations",
"limits",
"capabilities",
"randomness",
"creativity"
] | 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{
west2025base,
title={Base Models Beat Aligned Models at Randomness and Creativity},
author={Peter West and Christopher Potts},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=vqN8uom4A1}
} | west|base_models_beat_aligned_models_at_randomness_and_creativity | null | null | null | null | null | |
Improving Table Understanding with LLMs and Entity-Oriented Search | We introduce an entity-oriented search method to enhance table understanding in LLMs, reducing preprocessing and achieving state-of-the-art results. | Our work addresses the challenges of understanding tables. Existing methods often struggle with the unpredictable nature of table content, leading to a reliance on preprocessing and keyword matching. They also face limitations due to the lack of contextual information, which complicates the reasoning processes of large... | [
"Thi-Nhung Nguyen",
"Hoang Ngo",
"Dinh Phung",
"Thuy-Trang Vu",
"Dat Quoc Nguyen"
] | https://openreview.net/forum?id=vlyl9xZVAL | vlyl9xZVAL | vlyl9xZVAL | [
"~Thi-Nhung_Nguyen1",
"~Hoang_Ngo1",
"~Dinh_Phung2",
"~Thuy-Trang_Vu1",
"~Dat_Quoc_Nguyen1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/68932df0b9be8315ff4155a7db786fcffd032e2b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"table understanding",
"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{
nguyen2025improving,
title={Improving Table Understanding with {LLM}s and Entity-Oriented Search},
author={Thi-Nhung Nguyen and Hoang Ngo and Dinh Phung and Thuy-Trang Vu and Dat Quoc Nguyen},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=vlyl9xZVA... | nguyen|improving_table_understanding_with_llms_and_entityoriented_search | null | null | null | null | null | |
Positional Biases Shift as Inputs Approach Context Window Limits | This paper examines how input length, relative to a model’s context window, affects positional biases in LLMs. | Large Language Models (LLMs) often struggle to use information across long inputs effectively.
Prior work has identified positional biases, such as the Lost in the Middle (LiM) effect, where models perform better when information appears at the beginning (primacy bias) or end (recency bias) of the input, rather than i... | [
"Blerta Veseli",
"Julian Chibane",
"Mariya Toneva",
"Alexander Koller"
] | https://openreview.net/forum?id=vlUk8z8LaM | vlUk8z8LaM | vlUk8z8LaM | [
"~Blerta_Veseli1",
"~Julian_Chibane1",
"~Mariya_Toneva1",
"~Alexander_Koller2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/1fa87a52bb87f4535aa4c24f858f215c6d329083.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Long-context understanding",
"positional biases"
] | 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{
veseli2025positional,
title={Positional Biases Shift as Inputs Approach Context Window Limits},
author={Blerta Veseli and Julian Chibane and Mariya Toneva and Alexander Koller},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=vlUk8z8LaM}
} | veseli|positional_biases_shift_as_inputs_approach_context_window_limits | null | null | null | null | null | |
Agree to Disagree? A Meta-Evaluation of LLM Misgendering | We conduct a systematic meta-evaluation of different methods for measuring LLM misgendering across three datasets and find that they can disagree. | Numerous methods have been proposed to measure LLM misgendering, including probability-based evaluations (e.g., automatically with templatic sentences) and generation-based evaluations (e.g., with automatic heuristics or human validation).
However, it has gone unexamined whether these evaluation methods have convergent... | [
"Arjun Subramonian",
"Vagrant Gautam",
"Preethi Seshadri",
"Dietrich Klakow",
"Kai-Wei Chang",
"Yizhou Sun"
] | https://openreview.net/forum?id=vgmiRvpCLA | vgmiRvpCLA | vgmiRvpCLA | [
"~Arjun_Subramonian1",
"~Vagrant_Gautam1",
"~Preethi_Seshadri2",
"~Dietrich_Klakow1",
"~Kai-Wei_Chang1",
"~Yizhou_Sun1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/26bde4c0897c899d2a27271ba979a953201f4f50.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"fairness",
"meta-evaluation",
"misgendering"
] | 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{
subramonian2025agree,
title={Agree to Disagree? A Meta-Evaluation of {LLM} Misgendering},
author={Arjun Subramonian and Vagrant Gautam and Preethi Seshadri and Dietrich Klakow and Kai-Wei Chang and Yizhou Sun},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/... | subramonian|agree_to_disagree_a_metaevaluation_of_llm_misgendering | null | null | null | null | null | |
Critique Fine-Tuning: Learning to Critique is More Effective than Learning to Imitate | We introduce Critique Fine-Tuning, a training method that teaches LM to critique responses, achieving better performance than SFT with fewer training samples and comparable results to RL methods. | Supervised Fine-Tuning (SFT) is commonly used to train language models to imitate annotated responses for given instructions. In this paper, we propose Critique Fine-Tuning (CFT), a method more effective than SFT for reasoning tasks. Instead of simply imitating correct responses, CFT trains models to critique noisy res... | [
"Yubo Wang",
"Xiang Yue",
"Wenhu Chen"
] | https://openreview.net/forum?id=vTAz44GgOA | vTAz44GgOA | vTAz44GgOA | [
"~Yubo_Wang9",
"~Xiang_Yue1",
"~Wenhu_Chen3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/dc57be85188955311eeeb6b9cad46b5469c6b35e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Reasoning",
"Large Language Model",
"Fine-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{
wang2025critique,
title={Critique Fine-Tuning: Learning to Critique is More Effective than Learning to Imitate},
author={Yubo Wang and Xiang Yue and Wenhu Chen},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=vTAz44GgOA}
} | wang|critique_finetuning_learning_to_critique_is_more_effective_than_learning_to_imitate | null | null | null | null | null | |
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild | The paper explores zero training with rule-based rewards for emergent chain-of-thought reasoning in smaller models, producing significant improvements in both reasoning accuracy and CoT length across all settings. | DeepSeek-R1 has shown that long chain-of-thought (CoT) reasoning can naturally emerge through a simple reinforcement learning (RL) framework with rule-based rewards, where the training may directly start from the base models—a paradigm referred to as zero RL training. Most recent efforts to reproduce zero RL training h... | [
"Weihao Zeng",
"Yuzhen Huang",
"Qian Liu",
"Wei Liu",
"Keqing He",
"Zejun MA",
"Junxian He"
] | https://openreview.net/forum?id=vSMCBUgrQj | vSMCBUgrQj | vSMCBUgrQj | [
"~Weihao_Zeng2",
"~Yuzhen_Huang2",
"~Qian_Liu2",
"~Wei_Liu25",
"~Keqing_He1",
"~Zejun_MA1",
"~Junxian_He1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/bbe20558d2168bcb2992d581750387291d026a34.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Reasoning",
"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{
zeng2025simplerlzoo,
title={Simple{RL}-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild},
author={Weihao Zeng and Yuzhen Huang and Qian Liu and Wei Liu and Keqing He and Zejun MA and Junxian He},
booktitle={Second Conference on Language Modeling},
year={2025},
u... | zeng|simplerlzoo_investigating_and_taming_zero_reinforcement_learning_for_open_base_models_in_the_wild | null | null | null | null | null | |
Do Large Language Models Have a Planning Theory of Mind? Evidence from MindGames: a Multi-Step Persuasion Task | Humans significantly outperform LLMs at our complex theory of mind task | Recent evidence suggests Large Language Models (LLMs) display Theory of Mind (ToM) abilities. Most ToM experiments place participants in a spectatorial role, wherein they predict and interpret other agents' behavior. However, human ToM also contributes to dynamically planning action and strategically intervening on oth... | [
"Jared Moore",
"Ned Cooper",
"Rasmus Overmark",
"Beba Cibralic",
"Cameron Robert Jones",
"Nick Haber"
] | https://openreview.net/forum?id=vNJbDhgrM4 | vNJbDhgrM4 | vNJbDhgrM4 | [
"~Jared_Moore1",
"~Ned_Cooper1",
"~Rasmus_Overmark1",
"~Beba_Cibralic1",
"~Cameron_Robert_Jones1",
"~Nick_Haber1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/5e63f274f962ce2282ab6b0841a50e9c17d911ec.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"theory of mind",
"planning",
"causal model",
"persuasion"
] | 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{
moore2025do,
title={Do Large Language Models Have a Planning Theory of Mind? Evidence from MindGames: a Multi-Step Persuasion Task},
author={Jared Moore and Ned Cooper and Rasmus Overmark and Beba Cibralic and Cameron Robert Jones and Nick Haber},
booktitle={Second Conference on Language Modeling},
year... | moore|do_large_language_models_have_a_planning_theory_of_mind_evidence_from_mindgames_a_multistep_persuasion_task | null | null | null | null | null | |
Do Biased Models Have Biased Thoughts? | This paper explores whether biased language models have biased reasoning, finding that their thought processes are not strongly linked to biased outputs. | The impressive performance of language models is undeniable. However, the presence of biases based on gender, race, socio-economic status, physical appearance, and sexual orientation makes the deployment of language models challenging. This paper studies the effect of chain-of-thought prompting, a recent approach that ... | [
"Swati Rajwal",
"Shivank Garg",
"Reem Abdel-Salam",
"Abdelrahman Zayed"
] | https://openreview.net/forum?id=vDr0RV3590 | vDr0RV3590 | vDr0RV3590 | [
"~Swati_Rajwal2",
"~Shivank_Garg1",
"~Reem_Abdel-Salam1",
"~Abdelrahman_Zayed1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ded6a3254f5a138cc7200d82253bd49853ededb2.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Bias in language models",
"Large Language Models",
"biased thoughts",
"Chain-of-Thought prompting"
] | 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{
rajwal2025do,
title={Do Biased Models Have Biased Thoughts?},
author={Swati Rajwal and Shivank Garg and Reem Abdel-Salam and Abdelrahman Zayed},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=vDr0RV3590}
} | rajwal|do_biased_models_have_biased_thoughts | null | null | null | null | null | |
How do language models learn facts? Dynamics, curricula and hallucinations | We analyze learning dynamics of language models on a synthetic memory task and show that they learn sequentially, that some data distribution properties lead to faster learning, and that hallucinations appear simulataneously to knowledge acquisition. | Large language models accumulate vast amounts of knowledge during their pre-training, yet the dynamics governing this acquisition remain poorly understood. This work investigates the learning dynamics of language models on a synthetic factual recall task, uncovering three key findings: First, language models learn in t... | [
"Nicolas Zucchet",
"Jorg Bornschein",
"Stephanie C.Y. Chan",
"Andrew Kyle Lampinen",
"Razvan Pascanu",
"Soham De"
] | https://openreview.net/forum?id=vBcGnragkr | vBcGnragkr | vBcGnragkr | [
"~Nicolas_Zucchet1",
"~Jorg_Bornschein1",
"~Stephanie_C.Y._Chan1",
"~Andrew_Kyle_Lampinen1",
"~Razvan_Pascanu1",
"~Soham_De2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/462209e2d72b398c2da64f53207c0eeea6740b0d.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"learning dynamics",
"factual recall",
"curricula",
"data distribution",
"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{
zucchet2025how,
title={How do language models learn facts? Dynamics, curricula and hallucinations},
author={Nicolas Zucchet and Jorg Bornschein and Stephanie C.Y. Chan and Andrew Kyle Lampinen and Razvan Pascanu and Soham De},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https:/... | zucchet|how_do_language_models_learn_facts_dynamics_curricula_and_hallucinations | null | null | null | null | null | |
News is More than a Collection of Facts: Moral Frame Preserving News Summarization | The first investigation in how LLMs can summarize news articles while preserving moral framing. | News articles are more than collections of facts; they reflect journalists' framing, shaping how events are presented to the audience. One key aspect of framing is the choice to write in (or quote verbatim) morally charged language as opposed to using neutral terms. This moral framing carries implicit judgments that au... | [
"Enrico Liscio",
"Michela Lorandi",
"Pradeep K. Murukannaiah"
] | https://openreview.net/forum?id=uzauWUW9u3 | uzauWUW9u3 | uzauWUW9u3 | [
"~Enrico_Liscio1",
"~Michela_Lorandi1",
"~Pradeep_K._Murukannaiah1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/6940325f5f0ed453a99c0b091dcc120b38f1a6f4.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLMs",
"news",
"summarization",
"morality",
"framing"
] | 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{
liscio2025news,
title={News is More than a Collection of Facts: Moral Frame Preserving News Summarization},
author={Enrico Liscio and Michela Lorandi and Pradeep K. Murukannaiah},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=uzauWUW9u3}
} | liscio|news_is_more_than_a_collection_of_facts_moral_frame_preserving_news_summarization | null | null | null | null | null | |
Pairwise or Pointwise? Evaluating Feedback Protocols for Bias in LLM-Based Evaluation | This work examines how feedback protocols (absolute scores vs. pairwise preferences) impact biases in LLM evaluations, revealing that absolute scoring is more robust to distractor features. | Large Language Models (LLMs) are widely used as proxies for human labelers in both training (Reinforcement Learning from AI Feedback) and large-scale response evaluation (LLM-as-a-judge). Alignment and evaluation are critical components in the development of reliable LLMs, and the choice of feedback protocol plays a ce... | [
"Tuhina Tripathi",
"Manya Wadhwa",
"Greg Durrett",
"Scott Niekum"
] | https://openreview.net/forum?id=uyX5Vnow3U | uyX5Vnow3U | uyX5Vnow3U | [
"~Tuhina_Tripathi1",
"~Manya_Wadhwa1",
"~Greg_Durrett1",
"~Scott_Niekum1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ac5ede1c4f3e38efcb8223c7e17ba3fb8949b2ee.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"evaluation",
"data",
"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{
tripathi2025pairwise,
title={Pairwise or Pointwise? Evaluating Feedback Protocols for Bias in {LLM}-Based Evaluation},
author={Tuhina Tripathi and Manya Wadhwa and Greg Durrett and Scott Niekum},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=uyX5Vn... | tripathi|pairwise_or_pointwise_evaluating_feedback_protocols_for_bias_in_llmbased_evaluation | null | null | null | null | null | |
Estimating Optimal Context Length for Hybrid Retrieval-augmented Multi-document Summarization | We present a novel method to estimate optimal context length for retrieval-augmented generation. Our estimate is a function of the retriever, summarizer and the downstream task. | Recent advances in long-context reasoning abilities of language models led to interesting applications in large-scale multi-document summarization. However, prior work has shown that these long-context models are not effective at their claimed context windows. To this end, retrieval-augmented systems provide an efficie... | [
"Adithya Pratapa",
"Teruko Mitamura"
] | https://openreview.net/forum?id=uh0Sf8yN7n | uh0Sf8yN7n | uh0Sf8yN7n | [
"~Adithya_Pratapa1",
"~Teruko_Mitamura1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/4e0303ac5eb0858029dfdcaa571f784512a0ccdf.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"retrieval-augmented generation",
"long-context",
"multi-document 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{
pratapa2025estimating,
title={Estimating Optimal Context Length for Hybrid Retrieval-augmented Multi-document Summarization},
author={Adithya Pratapa and Teruko Mitamura},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=uh0Sf8yN7n}
} | pratapa|estimating_optimal_context_length_for_hybrid_retrievalaugmented_multidocument_summarization | null | null | null | null | null | |
Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill? | Reasoning models can’t think critically when premise is missing. | We find that the response length of reasoning LLMs, whether trained by reinforcement learning or supervised learning, drastically increases for ill-posed questions with missing premises (MiP), ending up with redundant and ineffective thinking.
Such failures are against the ``test-time scaling law'' but have been w... | [
"Chenrui Fan",
"Ming Li",
"Lichao Sun",
"Tianyi Zhou"
] | https://openreview.net/forum?id=ufozo2Wc9e | ufozo2Wc9e | ufozo2Wc9e | [
"~Chenrui_Fan1",
"~Ming_Li18",
"~Lichao_Sun1",
"~Tianyi_Zhou2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/018bea3ab55d1c1e4c93295a221d9e746fe84514.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM",
"Reasoning Model",
"Overthinking",
"Abstain"
] | 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{
fan2025missing,
title={Missing Premise exacerbates Overthinking: Are Reasoning Models losing Critical Thinking Skill?},
author={Chenrui Fan and Ming Li and Lichao Sun and Tianyi Zhou},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=ufozo2Wc9e}
} | fan|missing_premise_exacerbates_overthinking_are_reasoning_models_losing_critical_thinking_skill | /attachment/825254c1747951fd04bf0c9067828ba4da07f36f.zip | null | null | null | null | |
Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics | We evaluate large language models on Olympiad-level mathematics, revealing their inability to produce rigorous and logically sound proofs despite occasional correct final answers. | Recent advancements in large language models (LLMs) have shown impressive progress in mathematical reasoning tasks. However, current evaluation benchmarks predominantly focus on the accuracy of final answers, often overlooking the logical rigor crucial for mathematical problem-solving. The claim that state-of-the-art L... | [
"Hamed Mahdavi",
"Alireza Hashemi",
"Majid Daliri",
"Pegah Mohammadipour",
"Alireza Farhadi",
"Samira Malek",
"Yekta Yazdanifard",
"Amir Khasahmadi",
"Vasant G Honavar"
] | https://openreview.net/forum?id=uXR2KsA4L9 | uXR2KsA4L9 | uXR2KsA4L9 | [
"~Hamed_Mahdavi1",
"~Alireza_Hashemi2",
"~Majid_Daliri1",
"~Pegah_Mohammadipour1",
"~Alireza_Farhadi2",
"~Samira_Malek1",
"~Yekta_Yazdanifard1",
"~Amir_Khasahmadi1",
"~Vasant_G_Honavar1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d53d2675aef66e061647aa4edbe85fe1f4104521.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Mathematical Reasoning",
"Human Evaluation",
"Reasoning Evaluation",
"Math Problem-Solving"
] | 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{
mahdavi2025brains,
title={Brains vs. Bytes: Evaluating {LLM} Proficiency in Olympiad Mathematics},
author={Hamed Mahdavi and Alireza Hashemi and Majid Daliri and Pegah Mohammadipour and Alireza Farhadi and Samira Malek and Yekta Yazdanifard and Amir Khasahmadi and Vasant G Honavar},
booktitle={Second Co... | mahdavi|brains_vs_bytes_evaluating_llm_proficiency_in_olympiad_mathematics | null | null | null | null | null | |
BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity | We propose BlockFFN, an effective MoE architecture more friendly for end-side acceleration, as well as its sparsity-aware training objectives and efficient acceleration kernels. | To alleviate the computational burden of large language models (LLMs), architectures with activation sparsity, represented by mixture-of-experts (MoE), have attracted increasing attention. However, the non-differentiable and inflexible routing of vanilla MoE hurts model performance. Moreover, while each token activates... | [
"Chenyang Song",
"Weilin Zhao",
"Xu Han",
"Chaojun Xiao",
"Yingfa Chen",
"Yuxuan Li",
"Zhiyuan Liu",
"Maosong Sun"
] | https://openreview.net/forum?id=uLl7tSUOir | uLl7tSUOir | uLl7tSUOir | [
"~Chenyang_Song1",
"~Weilin_Zhao1",
"~Xu_Han2",
"~Chaojun_Xiao1",
"~Yingfa_Chen1",
"~Yuxuan_Li19",
"~Zhiyuan_Liu1",
"~Maosong_Sun1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/894e65b966a485306b765993e6715a25060f8737.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"mixture-of-experts",
"activation sparsity",
"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{
song2025blockffn,
title={Block{FFN}: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity},
author={Chenyang Song and Weilin Zhao and Xu Han and Chaojun Xiao and Yingfa Chen and Yuxuan Li and Zhiyuan Liu and Maosong Sun},
booktitle={Second Conference on Language... | song|blockffn_towards_endside_accelerationfriendly_mixtureofexperts_with_chunklevel_activation_sparsity | /attachment/64657ad2b7008be33d41cfe2edd34b44a1e24875.zip | null | null | null | null | |
ProsodyLM: Uncovering the Emerging Prosody Processing Capabilities in Speech Language Models | We propose ProsodyLM, a speech language model that demonstrate impressive emerging prosody generation and understand capabilities simply through pre-training on 30k audiobooks. | Speech language models refer to language models with speech processing and understanding capabilities. One key desirable capability for speech language models is the ability to capture the intricate interdependency between content and prosody. The existing mainstream paradigm of training speech language models, which c... | [
"Kaizhi Qian",
"Xulin Fan",
"Junrui Ni",
"Slava Shechtman",
"Mark A. Hasegawa-Johnson",
"Chuang Gan",
"Yang Zhang"
] | https://openreview.net/forum?id=uBg8PClMUu | uBg8PClMUu | uBg8PClMUu | [
"~Kaizhi_Qian1",
"~Xulin_Fan1",
"~Junrui_Ni1",
"~Slava_Shechtman1",
"~Mark_A._Hasegawa-Johnson1",
"~Chuang_Gan1",
"~Yang_Zhang3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/6a359ebba5a3de8baa31631883a6b21c9cbc97a3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Speech LM: Multi-modal 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{
qian2025prosodylm,
title={Prosody{LM}: Uncovering the Emerging Prosody Processing Capabilities in Speech Language Models},
author={Kaizhi Qian and Xulin Fan and Junrui Ni and Slava Shechtman and Mark A. Hasegawa-Johnson and Chuang Gan and Yang Zhang},
booktitle={Second Conference on Language Modeling},
... | qian|prosodylm_uncovering_the_emerging_prosody_processing_capabilities_in_speech_language_models | null | null | null | null | null | |
VaPR - Vision-language Preference alignment for Reasoning | VaPR, a hard-negative preference dataset that mitigates stylistic and length biases in AI feedback, enabling improved reasoning and robustness in preference finetuned (DPO) vision-language models across ten benchmarks. | Preference finetuning methods like Direct Preference Optimization (DPO) with AI-generated feedback have shown promise in aligning Large Vision-Language Models (LVLMs) with human preferences. However, existing techniques overlook the prevalence of noise in synthetic preference annotations in the form of stylistic and le... | [
"Rohan Wadhawan",
"Fabrice Y Harel-Canada",
"Zi-Yi Dou",
"Suhaila Shakiah",
"Robinson Piramuthu",
"Nanyun Peng"
] | https://openreview.net/forum?id=uBAubFwymy | uBAubFwymy | uBAubFwymy | [
"~Rohan_Wadhawan1",
"~Fabrice_Y_Harel-Canada1",
"~Zi-Yi_Dou1",
"~Suhaila_Shakiah1",
"~Robinson_Piramuthu1",
"~Nanyun_Peng1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/70b7995114502f1826a2a3c5a3f55008f8261306.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Vision Language Models",
"Preference Optimization",
"DPO",
"Data Generation",
"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{
wadhawan2025vapr,
title={Va{PR} - Vision-language Preference alignment for Reasoning},
author={Rohan Wadhawan and Fabrice Y Harel-Canada and Zi-Yi Dou and Suhaila Shakiah and Robinson Piramuthu and Nanyun Peng},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net... | wadhawan|vapr_visionlanguage_preference_alignment_for_reasoning | null | null | null | null | null | |
DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning | DeepRetrieval trains query generation models through reinforcement learning instead of supervised data, achieving state-of-the-art performance across diverse retrieval tasks while being more efficient than existing approaches. | Information retrieval systems are crucial for enabling effective access to large document collections. Recent approaches have leveraged Large Language Models (LLMs) to enhance retrieval performance through query augmentation, but often rely on expensive supervised learning or distillation techniques that require signif... | [
"Pengcheng Jiang",
"Jiacheng Lin",
"Lang Cao",
"Runchu Tian",
"SeongKu Kang",
"Zifeng Wang",
"Jimeng Sun",
"Jiawei Han"
] | https://openreview.net/forum?id=u9JXu4L17I | u9JXu4L17I | u9JXu4L17I | [
"~Pengcheng_Jiang2",
"~Jiacheng_Lin3",
"~Lang_Cao2",
"~Runchu_Tian1",
"~SeongKu_Kang1",
"~Zifeng_Wang3",
"~Jimeng_Sun3",
"~Jiawei_Han1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d6e93b6b5f6f01c6793b460b37410d7d7ec3a1cd.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Information Retrieval",
"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{
jiang2025deepretrieval,
title={DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning},
author={Pengcheng Jiang and Jiacheng Lin and Lang Cao and Runchu Tian and SeongKu Kang and Zifeng Wang and Jimeng Sun and Jiawei Han},
booktitle={Second Confer... | jiang|deepretrieval_hacking_real_search_engines_and_retrievers_with_large_language_models_via_reinforcement_learning | /attachment/e1c13f35faae5175020c5266f60439cdda5f1f8f.zip | null | null | null | null | |
SecurityLingua: Efficient Defense of LLM Jailbreak Attacks via Security-Aware Prompt Compression | SecurityLingua defends LLMs from jailbreak attacks using secutriy-aware prompt compression to extract the true intention. It helps the model activate its safety guardrails without altering the original prompt in minimal compute and latency overhead. | Large language models (LLMs) have achieved widespread adoption across numerous applications. However, many LLMs are vulnerable to malicious attacks even after safety alignment. These attacks typically bypass LLMs’ safety guardrails by wrapping the original malicious instructions inside adversarial jailbreaks prompts. P... | [
"Yucheng Li",
"Surin Ahn",
"Huiqiang Jiang",
"Amir H. Abdi",
"Yuqing Yang",
"Lili Qiu"
] | https://openreview.net/forum?id=tybbSo6wba | tybbSo6wba | tybbSo6wba | [
"~Yucheng_Li5",
"~Surin_Ahn1",
"~Huiqiang_Jiang2",
"~Amir_H._Abdi1",
"~Yuqing_Yang1",
"~Lili_Qiu3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d284f5f7d160ec273e8ba2c87857c7a6d07c1e91.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Jailbreak Attacks Defense",
"Prompt Compression"
] | 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{
li2025securitylingua,
title={SecurityLingua: Efficient Defense of {LLM} Jailbreak Attacks via Security-Aware Prompt Compression},
author={Yucheng Li and Surin Ahn and Huiqiang Jiang and Amir H. Abdi and Yuqing Yang and Lili Qiu},
booktitle={Second Conference on Language Modeling},
year={2025},
url={http... | li|securitylingua_efficient_defense_of_llm_jailbreak_attacks_via_securityaware_prompt_compression | null | null | null | null | null | |
Why do LLMs attend to the first token? | We study why it is useful for attention heads in LLMs to learn to "dump" most attention on the first token from an "over-mixing" perspective. | Large Language Models (LLMs) tend to attend heavily to the first token in the sequence -- creating a so-called attention sink. Many works have studied this phenomenon in detail, proposing various ways to either leverage or alleviate it. Attention sinks have been connected to quantisation difficulties, security issues, ... | [
"Federico Barbero",
"Alvaro Arroyo",
"Xiangming Gu",
"Christos Perivolaropoulos",
"Petar Veličković",
"Razvan Pascanu",
"Michael M. Bronstein"
] | https://openreview.net/forum?id=tu4dFUsW5z | tu4dFUsW5z | tu4dFUsW5z | [
"~Federico_Barbero1",
"~Alvaro_Arroyo1",
"~Xiangming_Gu1",
"~Christos_Perivolaropoulos1",
"~Petar_Veličković1",
"~Razvan_Pascanu1",
"~Michael_M._Bronstein1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/d2773cfb28982b55b4053eed019c7c33cd2cd57e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Attention Sinks",
"Information Propagation",
"Pre-training"
] | 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{
barbero2025why,
title={Why do {LLM}s attend to the first token?},
author={Federico Barbero and Alvaro Arroyo and Xiangming Gu and Christos Perivolaropoulos and Petar Veli{\v{c}}kovi{\'c} and Razvan Pascanu and Michael M. Bronstein},
booktitle={Second Conference on Language Modeling},
year={2025},
url={h... | barbero|why_do_llms_attend_to_the_first_token | null | null | null | null | null | |
Towards User-level Private Reinforcement Learning with Human Feedback | We propose AUP-RLHF, a user-level label DP framework that improves privacy-utility trade-offs in RLHF for better model alignment. | Reinforcement Learning with Human Feedback (RLHF) has emerged as an influential technique, enabling the alignment of large language models (LLMs) with human preferences. However, how to protect user preference privacy has become a crucial issue, as LLMs tend to remember users' preferences. Most previous work has focuse... | [
"Jiaming Zhang",
"Mingxi Lei",
"Meng Ding",
"Mengdi Li",
"Zihang Xiang",
"Difei Xu",
"Jinhui Xu",
"Di Wang"
] | https://openreview.net/forum?id=tfriX0r2Sg | tfriX0r2Sg | tfriX0r2Sg | [
"~Jiaming_Zhang15",
"~Mingxi_Lei1",
"~Meng_Ding3",
"~Mengdi_Li1",
"~Zihang_Xiang1",
"~Difei_Xu1",
"~Jinhui_Xu1",
"~Di_Wang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/0e585b4aba2e0dc85e2231ed96be5c03e85c9e0a.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Differential Privacy",
"RLHF",
"LLM 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{
zhang2025towards,
title={Towards User-level Private Reinforcement Learning with Human Feedback},
author={Jiaming Zhang and Mingxi Lei and Meng Ding and Mengdi Li and Zihang Xiang and Difei Xu and Jinhui Xu and Di Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openre... | zhang|towards_userlevel_private_reinforcement_learning_with_human_feedback | null | null | null | null | null | |
A Taxonomy of Transcendence | We propose a controlled setting in which to study how properties of the pretraining data influence the model's ability to transcend the performance of the sources that generated the data. | Although language models are trained to mimic humans, the resulting systems display capabilities beyond the scope of any one person. To understand this phenomenon, we use a controlled setting to identify properties of the training data that lead a model to transcend the performance of its data sources. We build on prev... | [
"Natalie Abreu",
"Edwin Zhang",
"Eran Malach",
"Naomi Saphra"
] | https://openreview.net/forum?id=tfTn8616Gf | tfTn8616Gf | tfTn8616Gf | [
"~Natalie_Abreu1",
"~Edwin_Zhang2",
"~Eran_Malach3",
"~Naomi_Saphra1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/fff295ffa555a1dfea26a3b7a268e1aee1446901.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"language models",
"data diversity",
"composition",
"knowledge graph"
] | 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{
abreu2025a,
title={A Taxonomy of Transcendence},
author={Natalie Abreu and Edwin Zhang and Eran Malach and Naomi Saphra},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=tfTn8616Gf}
} | abreu|a_taxonomy_of_transcendence | null | true | null | null | null | |
One-shot Optimized Steering Vectors Mediate Safety-relevant Behaviors in LLMs | Optimizing steering vectors on a single training example can yield vectors that modulate safety-relevant behavior in LLMs across wider datasets. | Steering vectors (SVs) have emerged as a promising approach for interpreting and controlling LLMs, but current methods typically require large contrastive datasets that are often impractical to construct and may capture spurious correlations.
We propose directly optimizing SVs through gradient descent on a single train... | [
"Jacob Dunefsky",
"Arman Cohan"
] | https://openreview.net/forum?id=teW4nIZ1gy | teW4nIZ1gy | teW4nIZ1gy | [
"~Jacob_Dunefsky1",
"~Arman_Cohan1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/2883e1c44b20ed2b5c2c316e1e3e525427dc9ea4.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"steering vectors",
"interpretability",
"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{
dunefsky2025oneshot,
title={One-shot Optimized Steering Vectors Mediate Safety-relevant Behaviors in {LLM}s},
author={Jacob Dunefsky and Arman Cohan},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=teW4nIZ1gy}
} | dunefsky|oneshot_optimized_steering_vectors_mediate_safetyrelevant_behaviors_in_llms | null | null | null | null | null | |
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts | This paper explores sparse adapters as a simpler and more effective building block for modular, parameter-efficient architectures, demonstrating superior model merging performance at scale. | Merging parameter-efficient task experts has recently gained growing attention as a way to build modular architectures that can be rapidly adapted on the fly for specific downstream tasks, without requiring additional fine-tuning. Typically, LoRA serves as the foundational building block of such parameter-efficient mod... | [
"Samin Yeasar Arnob",
"Zhan Su",
"Minseon Kim",
"Oleksiy Ostapenko",
"Riyasat Ohib",
"Esra'a Saleh",
"Doina Precup",
"Lucas Caccia",
"Alessandro Sordoni"
] | https://openreview.net/forum?id=te7UC87Zbw | te7UC87Zbw | te7UC87Zbw | [
"~Samin_Yeasar_Arnob1",
"~Zhan_Su1",
"~Minseon_Kim1",
"~Oleksiy_Ostapenko1",
"~Riyasat_Ohib1",
"~Esra'a_Saleh1",
"~Doina_Precup1",
"~Lucas_Caccia1",
"~Alessandro_Sordoni2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/324e2b7704b42932f84dc53ff4f42c928cf4026b.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Sparse adapter",
"Parameter-efficient finetuning",
"Model merging",
"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{
arnob2025exploring,
title={Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts},
author={Samin Yeasar Arnob and Zhan Su and Minseon Kim and Oleksiy Ostapenko and Riyasat Ohib and Esra'a Saleh and Doina Precup and Lucas Caccia and Alessandro Sordoni},
booktitle={Second Conferenc... | arnob|exploring_sparse_adapters_for_scalable_merging_of_parameter_efficient_experts | null | null | null | null | null | |
SpectR: Dynamically Composing LM Experts with Spectral Routing | SpectR is an approach for routing and merging existing LoRA models per-token and per-layer, without any additional training or data. | Training large, general-purpose language models poses significant challenges. The growing availability of specialized *expert* models, fine-tuned from pretrained models for specific tasks or domains, offers a promising alternative. Leveraging the potential of these existing expert models in real-world applications requ... | [
"William Fleshman",
"Benjamin Van Durme"
] | https://openreview.net/forum?id=tK8GHR62EX | tK8GHR62EX | tK8GHR62EX | [
"~William_Fleshman1",
"~Benjamin_Van_Durme2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/42fc2228d1fe25af7d5337cee4d3d171e0dd3f67.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"MoE",
"routing",
"merging",
"LoRA",
"adapters",
"experts"
] | 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{
fleshman2025spectr,
title={SpectR: Dynamically Composing {LM} Experts with Spectral Routing},
author={William Fleshman and Benjamin Van Durme},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=tK8GHR62EX}
} | fleshman|spectr_dynamically_composing_lm_experts_with_spectral_routing | null | null | null | null | null | |
D3: A Dataset for Training Code LMs to Act Diff-by-Diff | D3 is a dataset of 8 billion tokens of file-diff-sequence examples sampled from 850k Human-written source files, improving LM performance on code synthesis, completion, & editing. | We introduce D3 ("Diverse Data for Diff-by-Diff Coding"), a large dataset for training LMs to iteratively synthesize general-purpose Python source code by generating file diffs. D3 frames code synthesis as a goal-conditioned sequential decision-making problem, where goals, states, and actions are represented by token s... | [
"Ulyana Piterbarg",
"Kanishk Gandhi",
"Lerrel Pinto",
"Noah Goodman",
"Rob Fergus"
] | https://openreview.net/forum?id=sy71y74U80 | sy71y74U80 | sy71y74U80 | [
"~Ulyana_Piterbarg1",
"~Kanishk_Gandhi1",
"~Lerrel_Pinto1",
"~Noah_Goodman1",
"~Rob_Fergus1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/1b948345ea00973ec21fbc561eeaeadf9a67a160.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"data filtering",
"synthetic data",
"code synthesis",
"code editing",
"file diffs",
"midtraining",
"SFT",
"LM 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{
piterbarg2025d,
title={D3: A Dataset for Training Code {LM}s to Act Diff-by-Diff},
author={Ulyana Piterbarg and Kanishk Gandhi and Lerrel Pinto and Noah Goodman and Rob Fergus},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=sy71y74U80}
} | piterbarg|d3_a_dataset_for_training_code_lms_to_act_diffbydiff | /attachment/db1dce296e8bcb2b3440badc8ce5c55718a09742.zip | null | null | null | null | |
Supposedly Equivalent Facts That Aren’t? Entity Frequency in Pre-training Induces Asymmetry in LLMs | This work demonstrates that the asymmetry in how large language models recognise equivalent facts stems from inherent biases in their pre-training data, particularly through differences in entity frequency. | Understanding and mitigating hallucinations in Large Language Models (LLMs) is crucial for ensuring reliable content generation. While previous research has primarily focused on "when" LLMs hallucinate, our work explains "why" and directly links model behaviour to the pre-training data that forms their prior knowledge.... | [
"Yuan He",
"Bailan He",
"Zifeng Ding",
"Alisia Maria Lupidi",
"Yuqicheng Zhu",
"Shuo Chen",
"Caiqi Zhang",
"Jiaoyan Chen",
"Yunpu Ma",
"Volker Tresp",
"Ian Horrocks"
] | https://openreview.net/forum?id=sX4OoLKSW2 | sX4OoLKSW2 | sX4OoLKSW2 | [
"~Yuan_He5",
"~Bailan_He1",
"~Zifeng_Ding1",
"~Alisia_Maria_Lupidi1",
"~Yuqicheng_Zhu1",
"~Shuo_Chen12",
"~Caiqi_Zhang2",
"~Jiaoyan_Chen1",
"~Yunpu_Ma1",
"~Volker_Tresp1",
"~Ian_Horrocks1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/469c6230650e22a6dcdd88b9c5a78eb97a921679.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Asymmetry",
"Equivalent Facts",
"Entity Frequency",
"Pre-training Bias",
"Knowledge Probing",
"Hallucinations",
"Knowledge Graphs"
] | 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{
he2025supposedly,
title={Supposedly Equivalent Facts That Aren{\textquoteright}t? Entity Frequency in Pre-training Induces Asymmetry in {LLM}s},
author={Yuan He and Bailan He and Zifeng Ding and Alisia Maria Lupidi and Yuqicheng Zhu and Shuo Chen and Caiqi Zhang and Jiaoyan Chen and Yunpu Ma and Volker ... | he|supposedly_equivalent_facts_that_arent_entity_frequency_in_pretraining_induces_asymmetry_in_llms | /attachment/e5908026cff40ccda236868d7ddebec90ec6823c.zip | null | null | null | null | |
Scalable Zeroth-Order Fine-Tuning for Extremely Large Language Models with Limited GPU Memory | ZO2 is a memory-efficient framework that enables zeroth-order fine-tuning of large language models like OPT-175B on a single 18GB GPU. | Fine-tuning large pre-trained LLMs generally demands extensive GPU memory. Traditional first-order optimizers like SGD encounter substantial difficulties due to increased memory requirements from storing activations and gradients during both the forward and backward phases as the model size expands. Alternatively, zero... | [
"Liangyu Wang",
"Jie Ren",
"Hang Xu",
"Junxiao Wang",
"Huanyi Xie",
"David E. Keyes",
"Di Wang"
] | https://openreview.net/forum?id=s0p9xpORgP | s0p9xpORgP | s0p9xpORgP | [
"~Liangyu_Wang1",
"~Jie_Ren4",
"~Hang_Xu3",
"~Junxiao_Wang1",
"~Huanyi_Xie1",
"~David_E._Keyes1",
"~Di_Wang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/12cdf783e09bc288a3a95641696d10ece8519c56.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Zeroth-Order Optimization",
"LLMs",
"Fine-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{
wang2025scalable,
title={Scalable Zeroth-Order Fine-Tuning for Extremely Large Language Models with Limited {GPU} Memory},
author={Liangyu Wang and Jie Ren and Hang Xu and Junxiao Wang and Huanyi Xie and David E. Keyes and Di Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={h... | wang|scalable_zerothorder_finetuning_for_extremely_large_language_models_with_limited_gpu_memory | /attachment/d1a8cbfa2abae3229e3889fc60a25827e31d5d45.zip | null | null | null | null | |
MLGym: A New Framework and Benchmark for Advancing AI Research Agents | MLGym introduces a framework and benchmark suite for evaluating and developing large language model agents on diverse AI research tasks. | We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. This is the first Gym environment for machine learning (ML) tasks, enabling research on reinforcement learning (RL) algorithms for training such agents. MLGym-bench consists of 13 diverse and... | [
"Deepak Nathani",
"Lovish Madaan",
"Nicholas Roberts",
"Nikolay Bashlykov",
"Ajay Menon",
"Vincent Moens",
"Mikhail Plekhanov",
"Amar Budhiraja",
"Despoina Magka",
"Vladislav Vorotilov",
"Gaurav Chaurasia",
"Dieuwke Hupkes",
"Ricardo Silveira Cabral",
"Tatiana Shavrina",
"Jakob Nicolaus ... | https://openreview.net/forum?id=ryTr83DxRq | ryTr83DxRq | ryTr83DxRq | [
"~Deepak_Nathani2",
"~Lovish_Madaan1",
"~Nicholas_Roberts2",
"~Nikolay_Bashlykov1",
"~Ajay_Menon1",
"~Vincent_Moens3",
"~Mikhail_Plekhanov1",
"~Amar_Budhiraja1",
"~Despoina_Magka2",
"~Vladislav_Vorotilov1",
"~Gaurav_Chaurasia1",
"~Dieuwke_Hupkes1",
"~Ricardo_Silveira_Cabral1",
"~Tatiana_Sh... | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/75f6e6aa5276a0b93fd3859ec7b41c92ee79cea8.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"LLM Agents",
"Tool Use",
"Benchmark",
"AI Research 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{
nathani2025mlgym,
title={{MLG}ym: A New Framework and Benchmark for Advancing {AI} Research Agents},
author={Deepak Nathani and Lovish Madaan and Nicholas Roberts and Nikolay Bashlykov and Ajay Menon and Vincent Moens and Mikhail Plekhanov and Amar Budhiraja and Despoina Magka and Vladislav Vorotilov an... | nathani|mlgym_a_new_framework_and_benchmark_for_advancing_ai_research_agents | null | null | null | null | null | |
AutoScale: Scale-Aware Data Mixing for Pre-Training LLMs | We propose AutoScale, which automatically predicts compute-optimal data compositions for training LLMs at the target training data scale. | Domain reweighting is an emerging research area aimed at adjusting the relative weights of different data sources to improve the effectiveness and efficiency of LLM pre-training. We show that data mixtures that perform well at smaller scales may not retain their advantage at larger scales, challenging the existing prac... | [
"Feiyang Kang",
"Yifan Sun",
"Bingbing Wen",
"Si Chen",
"Dawn Song",
"Rafid Mahmood",
"Ruoxi Jia"
] | https://openreview.net/forum?id=rujwIvjooA | rujwIvjooA | rujwIvjooA | [
"~Feiyang_Kang1",
"~Yifan_Sun8",
"~Bingbing_Wen1",
"~Si_Chen5",
"~Dawn_Song1",
"~Rafid_Mahmood1",
"~Ruoxi_Jia1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/bcff10571bac9282299d471ff5a373c50aadd772.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models (LLM)",
"Data Curation",
"Domain Reweighting",
"Scaling Laws",
"Data-centric AI"
] | 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{
kang2025autoscale,
title={AutoScale: Scale-Aware Data Mixing for Pre-Training {LLM}s},
author={Feiyang Kang and Yifan Sun and Bingbing Wen and Si Chen and Dawn Song and Rafid Mahmood and Ruoxi Jia},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=ruj... | kang|autoscale_scaleaware_data_mixing_for_pretraining_llms | null | null | null | null | null | |
LongProc: Benchmarking Long-Context Language Models on Long Procedural Generation | We introduce LongProc (Long Procedural Generation), a new benchmark that requires both the integration of highly dispersed information and long-form generation. | Existing benchmarks for evaluating long-context language models (LCLMs) primarily focus on long-context recall, requiring models to produce short responses based on a few critical snippets while processing thousands of irrelevant tokens.
We introduce LongProc (Long Procedural Generation), a new benchmark that requires ... | [
"Xi Ye",
"Fangcong Yin",
"Yinghui He",
"Joie Zhang",
"Howard Yen",
"Tianyu Gao",
"Greg Durrett",
"Danqi Chen"
] | https://openreview.net/forum?id=ruWC5LIMSo | ruWC5LIMSo | ruWC5LIMSo | [
"~Xi_Ye2",
"~Fangcong_Yin1",
"~Yinghui_He1",
"~Joie_Zhang1",
"~Howard_Yen1",
"~Tianyu_Gao1",
"~Greg_Durrett1",
"~Danqi_Chen1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/7b139d89c8b6d0a334b5ce42efe3b6c75de299f9.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Keywords: Large language models",
"long-context",
"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{
ye2025longproc,
title={LongProc: Benchmarking Long-Context Language Models on Long Procedural Generation},
author={Xi Ye and Fangcong Yin and Yinghui He and Joie Zhang and Howard Yen and Tianyu Gao and Greg Durrett and Danqi Chen},
booktitle={Second Conference on Language Modeling},
year={2025},
url={ht... | ye|longproc_benchmarking_longcontext_language_models_on_long_procedural_generation | /attachment/38208434b51c7f317e26844b704854a0274f2798.zip | null | null | null | null | |
Unifying Autoregressive and Diffusion-Based Sequence Generation | We build upon diffusion language models to 1. make them autoregressive and 2. use an hybrid of the "uniform" and "absorb" token noising processes. | We present significant extensions to diffusion-based sequence generation models, blurring the line with autoregressive language models.
We introduce *hyperschedules*, which assign distinct noise schedules to individual token positions, generalizing both autoregressive models (*e.g.*, GPT) and conventional diffusion mod... | [
"Nima Fathi",
"Torsten Scholak",
"Pierre-Andre Noel"
] | https://openreview.net/forum?id=rgq9BFXSFl | rgq9BFXSFl | rgq9BFXSFl | [
"~Nima_Fathi1",
"~Torsten_Scholak1",
"~Pierre-Andre_Noel1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/b3ac37815e8b729f1792c2e3a44ab3d9748d4e20.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"discrete diffusion",
"generative diffusion models",
"language models",
"autoregressive 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{
fathi2025unifying,
title={Unifying Autoregressive and Diffusion-Based Sequence Generation},
author={Nima Fathi and Torsten Scholak and Pierre-Andre Noel},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=rgq9BFXSFl}
} | fathi|unifying_autoregressive_and_diffusionbased_sequence_generation | null | null | null | null | null | |
RankAlign: A Ranking View of the Generator-Validator Gap in Large Language Models | We reduce the generator-validator gap (a discrepancy between LLMs' generated answers and self-verification), with a ranking-based loss function, improving model consistency | Although large language models (LLMs) have become more capable and accurate across many tasks, some fundamental sources of unreliability remain in their behavior. One key limitation is their inconsistency at reporting the same information when prompts are changed. In this paper, we consider the discrepancy between a mo... | [
"Juan Diego Rodriguez",
"Wenxuan Ding",
"Katrin Erk",
"Greg Durrett"
] | https://openreview.net/forum?id=rJOkPauru9 | rJOkPauru9 | rJOkPauru9 | [
"~Juan_Diego_Rodriguez1",
"~Wenxuan_Ding1",
"~Katrin_Erk1",
"~Greg_Durrett1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/445e32b946f6a1089e85265a3388edb5f9cac631.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"consistency",
"robustness",
"ranking loss",
"generalizability",
"generator-validator gap"
] | 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{
rodriguez2025rankalign,
title={RankAlign: A Ranking View of the Generator-Validator Gap in Large Language Models},
author={Juan Diego Rodriguez and Wenxuan Ding and Katrin Erk and Greg Durrett},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=rJOkPau... | rodriguez|rankalign_a_ranking_view_of_the_generatorvalidator_gap_in_large_language_models | null | null | null | null | null | |
Contextualize-then-Aggregate: Circuits for In-Context Learning in Gemma-2 2B | We use causal interventions to uncover a two-step strategy used to assemble task information from the fewshot examples in a prompt. | In-Context Learning (ICL) is an intriguing ability of large language models (LLMs). Despite a substantial amount of work on its behavioral aspects and how it emerges in miniature setups, it remains unclear which mechanism assembles task information from the individual examples in a fewshot prompt. We use causal interve... | [
"Aleksandra Bakalova",
"Yana Veitsman",
"Xinting Huang",
"Michael Hahn"
] | https://openreview.net/forum?id=rGNAyHReSg | rGNAyHReSg | rGNAyHReSg | [
"~Aleksandra_Bakalova2",
"~Yana_Veitsman1",
"~Xinting_Huang2",
"~Michael_Hahn1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/0e90ec68695e0ca24ed0d342de1795113dc8b7fa.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"In-Context Learning",
"Mechanistic 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{
bakalova2025contextualizethenaggregate,
title={Contextualize-then-Aggregate: Circuits for In-Context Learning in Gemma-2 2B},
author={Aleksandra Bakalova and Yana Veitsman and Xinting Huang and Michael Hahn},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/fo... | bakalova|contextualizethenaggregate_circuits_for_incontext_learning_in_gemma2_2b | /attachment/264eaf273f446b8b60871c95b423bf71648a3819.zip | null | null | null | null | |
When Splitting Makes Stronger: A Theoretical and Empirical Analysis of Divide-and-Conquer Prompting in LLMs | This paper examines when divide-and-conquer (DaC) prompting is beneficial for LLMs. Through theoretical and empirical analysis, we identify specific task types where breaking inputs into sub-parts improves performance. | Foundation models, particularly Large Language Models (LLMs), have garnered significant interest due to their wide range of applications. Yet these models demonstrate notable weaknesses when confronted with tasks involving iterative sub-problems or deliberately misleading content—exemplified by complex arithmetic oper... | [
"Yizhou Zhang",
"Defu Cao",
"Lun Du",
"Qiang Fu",
"Yan Liu"
] | https://openreview.net/forum?id=rAR7iPI8Kh | rAR7iPI8Kh | rAR7iPI8Kh | [
"~Yizhou_Zhang3",
"~Defu_Cao1",
"~Lun_Du1",
"~Qiang_Fu7",
"~Yan_Liu1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e08ca1a770c51d4f6e6353307b900deabf548fcb.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Program-guided Prompt",
"Divide-and-Conquer",
"Foundation Model",
"Large Language Models",
"Deceptive content"
] | 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{
zhang2025when,
title={When Splitting Makes Stronger: A Theoretical and Empirical Analysis of Divide-and-Conquer Prompting in {LLM}s},
author={Yizhou Zhang and Defu Cao and Lun Du and Qiang Fu and Yan Liu},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum... | zhang|when_splitting_makes_stronger_a_theoretical_and_empirical_analysis_of_divideandconquer_prompting_in_llms | null | null | null | null | null | |
ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations | ScholarCopilot is a language model that combines text generation and citation retrieval for academic writing | Academic writing requires both coherent text generation and precise citation of relevant literature. Although recent Retrieval-Augmented Generation (RAG) systems have significantly improved factual accuracy in general-purpose text generation, their ability to support professional academic writing remains limited. In th... | [
"Yubo Wang",
"Xueguang Ma",
"Ping Nie",
"Huaye Zeng",
"Zhiheng Lyu",
"Yuxuan Zhang",
"Benjamin Schneider",
"Yi Lu",
"Xiang Yue",
"Wenhu Chen"
] | https://openreview.net/forum?id=r8nloXtluk | r8nloXtluk | r8nloXtluk | [
"~Yubo_Wang9",
"~Xueguang_Ma1",
"~Ping_Nie1",
"~Huaye_Zeng2",
"~Zhiheng_Lyu2",
"~Yuxuan_Zhang12",
"~Benjamin_Schneider1",
"~Yi_Lu9",
"~Xiang_Yue1",
"~Wenhu_Chen3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/7ea1b2c5ff292ac8983dfe38db0674217a2fa774.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"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{
wang2025scholarcopilot,
title={ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations},
author={Yubo Wang and Xueguang Ma and Ping Nie and Huaye Zeng and Zhiheng Lyu and Yuxuan Zhang and Benjamin Schneider and Yi Lu and Xiang Yue and Wenhu Chen},
booktitle={Second Co... | wang|scholarcopilot_training_large_language_models_for_academic_writing_with_accurate_citations | null | null | null | null | null | |
TRELLIS: Learning to Compress Key-Value Memory in Attention Models | This paper introduces a novel approach to efficiently compress the K-V cache into a fixed number of slots | Transformers, while powerful, suffer from quadratic computational complexity and the ever-growing Key-Value (KV) cache of the attention mechanism. This paper introduces Trellis, a novel Transformer architecture with bounded memory that learns how to compress its key-value memory dynamically at test time. Trellis repla... | [
"Mahdi Karami",
"Ali Behrouz",
"Praneeth Kacham",
"Vahab Mirrokni"
] | https://openreview.net/forum?id=r61s1FNYlj | r61s1FNYlj | r61s1FNYlj | [
"~Mahdi_Karami2",
"~Ali_Behrouz1",
"~Praneeth_Kacham1",
"~Vahab_Mirrokni2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/05db279bb86af77d3beccbd36e9cbc4df6822121.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Sequence Models",
"Language models",
"Recurrent Neural Nets",
"Test Time Training"
] | 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{
karami2025trellis,
title={{TRELLIS}: Learning to Compress Key-Value Memory in Attention Models},
author={Mahdi Karami and Ali Behrouz and Praneeth Kacham and Vahab Mirrokni},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=r61s1FNYlj}
} | karami|trellis_learning_to_compress_keyvalue_memory_in_attention_models | null | null | null | null | null | |
LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K | LV-Eval is a long-context benchmark with 5 length levels up to 256K. It's designed to be challenging, suitable for controllable comparison, and mitigates knowledge leakage issue in evaluation. | State-of-the-art large language models (LLMs) are now claiming remarkable supported context lengths of 256k or even more. In contrast, the average context lengths of mainstream benchmarks are insufficient (5k-21k), and they suffer from potential knowledge leakage and inaccurate metrics, resulting in biased evaluation. ... | [
"Tao Yuan",
"Xuefei Ning",
"Dong Zhou",
"Zhijie Yang",
"Shiyao Li",
"Minghui Zhuang",
"Zheyue Tan",
"Zhuyu Yao",
"Dahua Lin",
"Boxun Li",
"Guohao Dai",
"Shengen Yan",
"Yu Wang"
] | https://openreview.net/forum?id=r0AXK5Cnhr | r0AXK5Cnhr | r0AXK5Cnhr | [
"~Tao_Yuan7",
"~Xuefei_Ning1",
"~Dong_Zhou8",
"~Zhijie_Yang3",
"~Shiyao_Li2",
"~Minghui_Zhuang1",
"~Zheyue_Tan1",
"~Zhuyu_Yao1",
"~Dahua_Lin1",
"~Boxun_Li2",
"~Guohao_Dai4",
"~Shengen_Yan1",
"~Yu_Wang3"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ebb97f30ec2136677483b21d1a5838ec8cc0a23a.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"large language model",
"long-context benchmark",
"knowledge leakage mitigation"
] | 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{
yuan2025lveval,
title={{LV}-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K},
author={Tao Yuan and Xuefei Ning and Dong Zhou and Zhijie Yang and Shiyao Li and Minghui Zhuang and Zheyue Tan and Zhuyu Yao and Dahua Lin and Boxun Li and Guohao Dai and Shengen Yan and Yu Wang},
bookt... | yuan|lveval_a_balanced_longcontext_benchmark_with_5_length_levels_up_to_256k | null | null | null | null | null | |
Texture or Semantics? Vision-Language Models Get Lost in Font Recognition | We introduce a special two-level benchmark to assess VLMs’ font recognition abilities. The results indicate that VLMs perform poorly on font recognition tasks and are easily influenced by visual cues rather than semantic understanding. | Modern Vision-Language Models (VLMs) exhibit remarkable visual and linguistic capabilities, achieving impressive performance in various tasks such as image recognition and object localization. However, their effectiveness in fine-grained tasks remains an open question. In everyday scenarios, individuals encountering de... | [
"Zhecheng Li",
"Guoxian Song",
"Yujun Cai",
"Zhen Xiong",
"Junsong Yuan",
"Yiwei Wang"
] | https://openreview.net/forum?id=qiLJVU4I8P | qiLJVU4I8P | qiLJVU4I8P | [
"~Zhecheng_Li1",
"~Guoxian_Song1",
"~Yujun_Cai1",
"~Zhen_Xiong2",
"~Junsong_Yuan2",
"~Yiwei_Wang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/a6aed302b07a25b72eadc5f77edb021f5876fa54.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"vision language models",
"font recognition",
"texture or semantics",
"stroop effect"
] | 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{
li2025texture,
title={Texture or Semantics? Vision-Language Models Get Lost in Font Recognition},
author={Zhecheng Li and Guoxian Song and Yujun Cai and Zhen Xiong and Junsong Yuan and Yiwei Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=qiLJ... | li|texture_or_semantics_visionlanguage_models_get_lost_in_font_recognition | null | null | null | null | null | |
REM: Evaluating LLM Embodied Spatial Reasoning through Multi-Frame Trajectories | We introduce REM, a benchmark revealing that current multimodal language models lack fundamental abilities in spatial reasoning, object permanence, and tracking objects over changing viewpoints. | Humans build viewpoint-independent cognitive maps through navigation, enabling intuitive reasoning about object permanence and spatial relations. We argue that multimodal large language models (MLLMs), despite extensive video training, lack this fundamental spatial reasoning capability, a critical limitation for embodi... | [
"Jacob Thompson",
"Emiliano Garcia-Lopez",
"Yonatan Bisk"
] | https://openreview.net/forum?id=qbWpEufkqk | qbWpEufkqk | qbWpEufkqk | [
"~Jacob_Thompson1",
"~Emiliano_Garcia-Lopez1",
"~Yonatan_Bisk1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/f0632dcb2d7ef41f07f0cf67492a41d5a8622c95.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Multimodal Reasoning",
"Embodied AI",
"VLMs",
"Spatial Reasoning",
"Object Permanence",
"Visuospatial Representation",
"Large Language Models (LLMs)",
"Egocentric Vision",
"Video Understanding",
"Evaluation Benchmarks",
"Synthetic Environments",
"Long-horizon Reasoning",
"Numerical Tracking... | 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{
thompson2025rem,
title={{REM}: Evaluating {LLM} Embodied Spatial Reasoning through Multi-Frame Trajectories},
author={Jacob Thompson and Emiliano Garcia-Lopez and Yonatan Bisk},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=qbWpEufkqk}
} | thompson|rem_evaluating_llm_embodied_spatial_reasoning_through_multiframe_trajectories | null | null | null | null | null | |
ALOPE: Adaptive Layer Optimization for Translation Quality Estimation using Large Language Models | This paper presents ALOPE, an adaptive layer-optimization framework for LLM-based translation quality estimation, enhancing cross-lingual transfer learning through layer-wise adaptation, dynamic weighting, and multi-head regression. | Large Language Models (LLMs) have shown remarkable performance across a wide range of natural language processing tasks. Quality Estimation (QE) for Machine Translation (MT), which assesses the quality of a source-target pair without relying on reference translations, remains a challenging cross-lingual task for LLMs. ... | [
"Archchana Sindhujan",
"Shenbin Qian",
"Chan Chi Chun Matthew",
"Constantin Orasan",
"Diptesh Kanojia"
] | https://openreview.net/forum?id=qSFr5wJPGc | qSFr5wJPGc | qSFr5wJPGc | [
"~Archchana_Sindhujan1",
"~Shenbin_Qian1",
"~Chan_Chi_Chun_Matthew1",
"~Constantin_Orasan1",
"~Diptesh_Kanojia1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/506fd31916a1a4ae8559855c5d93d0291fd570c2.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Quality Estimation",
"Machine Translation",
"Translation Quality"
] | 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{
sindhujan2025alope,
title={{ALOPE}: Adaptive Layer Optimization for Translation Quality Estimation using Large Language Models},
author={Archchana Sindhujan and Shenbin Qian and Chan Chi Chun Matthew and Constantin Orasan and Diptesh Kanojia},
booktitle={Second Conference on Language Modeling},
year={20... | sindhujan|alope_adaptive_layer_optimization_for_translation_quality_estimation_using_large_language_models | null | null | null | null | null | |
Hidden in plain sight: VLMs overlook their visual representations | VLMs perform worse on vision-centric tasks than their underlying vision models, relying on their language priors instead. Improving their integration of visual data—not just adding stronger vision backbones—is key to unlocking their full potential. | Language provides a natural interface to specify and evaluate performance on visual tasks.
To realize this possibility, vision language models (VLMs) must successfully integrate visual and linguistic information.
Our work compares VLMs to a direct readout of their visual encoders to understand their ability to integra... | [
"Stephanie Fu",
"tyler bonnen",
"Devin Guillory",
"Trevor Darrell"
] | https://openreview.net/forum?id=qQb1JLrwol | qQb1JLrwol | qQb1JLrwol | [
"~Stephanie_Fu1",
"~tyler_bonnen1",
"~Devin_Guillory1",
"~Trevor_Darrell2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/74c909720993b9aa6a3d8e2e6f98ea5bea6cec00.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"vision",
"language",
"representation",
"benchmark",
"encoder",
"vlm"
] | 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{
fu2025hidden,
title={Hidden in plain sight: {VLM}s overlook their visual representations},
author={Stephanie Fu and tyler bonnen and Devin Guillory and Trevor Darrell},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=qQb1JLrwol}
} | fu|hidden_in_plain_sight_vlms_overlook_their_visual_representations | null | true | null | null | null | |
Interpreting the linear structure of vision-language model embedding spaces | We train and release sparse autoencoders on the joint vision-language spaces of four models, and examine what the linear concepts reveal about the joint organization of meaning and modality | Vision-language models encode images and text in a joint space, minimizing the distance between corresponding image and text pairs. How are language and images organized in this joint space, and how do the models encode meaning and modality? To investigate this, we train and release sparse autoencoders (SAEs) on the em... | [
"Isabel Papadimitriou",
"Huangyuan Su",
"Thomas Fel",
"Sham M. Kakade",
"Stephanie Gil"
] | https://openreview.net/forum?id=qPsmGjpq1j | qPsmGjpq1j | qPsmGjpq1j | [
"~Isabel_Papadimitriou1",
"~Huangyuan_Su1",
"~Thomas_Fel2",
"~Sham_M._Kakade1",
"~Stephanie_Gil2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/dd502e2e07e3a09b56182f616adadaa9c98e348c.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"vision-language models",
"interpretability",
"cross-modality meaning"
] | 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{
papadimitriou2025interpreting,
title={Interpreting the linear structure of vision-language model embedding spaces},
author={Isabel Papadimitriou and Huangyuan Su and Thomas Fel and Sham M. Kakade and Stephanie Gil},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview... | papadimitriou|interpreting_the_linear_structure_of_visionlanguage_model_embedding_spaces | null | null | null | null | null | |
SmolVLM: Redefining small and efficient multimodal models | We explore extremely efficient VLMs starting at 256M parameters, which run with less than 1GB | Large Vision-Language Models (VLMs) deliver exceptional performance but require significant computational resources, limiting their deployment on mobile and edge devices. Smaller VLMs typically mirror design choices of larger models, such as extensive image tokenization, leading to inefficient GPU memory usage and cons... | [
"Andrés Marafioti",
"Orr Zohar",
"Miquel Farré",
"Merve noyan",
"Elie Bakouch",
"Pedro Manuel Cuenca Jiménez",
"Cyril Zakka",
"Loubna Ben allal",
"Anton Lozhkov",
"Nouamane Tazi",
"Vaibhav Srivastav",
"Joshua Lochner",
"Hugo Larcher",
"Mathieu Morlon",
"Lewis Tunstall",
"Leandro Von We... | https://openreview.net/forum?id=qMUbhGUFUb | qMUbhGUFUb | qMUbhGUFUb | [
"~Andrés_Marafioti1",
"~Orr_Zohar1",
"~Miquel_Farré1",
"~Merve_noyan1",
"~Elie_Bakouch1",
"~Pedro_Manuel_Cuenca_Jiménez1",
"~Cyril_Zakka1",
"~Loubna_Ben_allal1",
"~Anton_Lozhkov1",
"~Nouamane_Tazi1",
"~Vaibhav_Srivastav2",
"~Joshua_Lochner1",
"~Hugo_Larcher1",
"~Mathieu_Morlon1",
"~Lewis... | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/ff0790564f57d670a9033629dfbdaa6328752eca.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Vision Language Models",
"Large Multimodal Models",
"Vision Understanding",
"Video Understanding"
] | 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{
marafioti2025smolvlm,
title={Smol{VLM}: Redefining small and efficient multimodal models},
author={Andr{\'e}s Marafioti and Orr Zohar and Miquel Farr{\'e} and Merve noyan and Elie Bakouch and Pedro Manuel Cuenca Jim{\'e}nez and Cyril Zakka and Loubna Ben allal and Anton Lozhkov and Nouamane Tazi and Vai... | marafioti|smolvlm_redefining_small_and_efficient_multimodal_models | /attachment/341f5c3957a28cc47659fed5751c69c213885514.zip | null | null | null | null | |
Benchmarking Retrieval-Augmented Generation for Chemistry | We construct a comprehensive Retrieval-Augmented Generation benchmark for chemistry. | Retrieval-augmented generation (RAG) has emerged as a powerful framework for enhancing large language models (LLMs) with external knowledge, particularly in scientific domains that demand specialized and dynamic information.
Despite its promise, the application of RAG in the chemistry domain remains underexplored, pri... | [
"Xianrui Zhong",
"Bowen Jin",
"Siru Ouyang",
"Yanzhen Shen",
"Qiao Jin",
"Yin Fang",
"Zhiyong Lu",
"Jiawei Han"
] | https://openreview.net/forum?id=qG4dL0bart | qG4dL0bart | qG4dL0bart | [
"~Xianrui_Zhong1",
"~Bowen_Jin1",
"~Siru_Ouyang1",
"~Yanzhen_Shen1",
"~Qiao_Jin1",
"~Yin_Fang1",
"~Zhiyong_Lu1",
"~Jiawei_Han1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/aecea758b388085e9dbf18bb16b4d7637b2a4709.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Retrieval-Augmented Generation",
"RAG",
"Benchmark",
"AI for Science",
"LLM",
"Large Language Model",
"Chemistry"
] | 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{
zhong2025benchmarking,
title={Benchmarking Retrieval-Augmented Generation for Chemistry},
author={Xianrui Zhong and Bowen Jin and Siru Ouyang and Yanzhen Shen and Qiao Jin and Yin Fang and Zhiyong Lu and Jiawei Han},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openrevie... | zhong|benchmarking_retrievalaugmented_generation_for_chemistry | null | null | null | null | null | |
Finding Flawed Fictions: Evaluating Complex Reasoning in Language Models via Plot Hole Detection | We propose an automatic method to generate stories with logical inconsistencies, which we then use to curate a benchmark to evaluate capabilities of LLMs towards reasoning for plot holes in stories. | Stories are a fundamental aspect of human experience. Engaging deeply with stories and spotting plot holes—inconsistencies in a storyline that break the internal logic or rules of a story’s world—requires nuanced reasoning skills, including tracking entities and events and their interplay, abstract thinking, pragmatic ... | [
"Kabir Ahuja",
"Melanie Sclar",
"Yulia Tsvetkov"
] | https://openreview.net/forum?id=ptmgWRCWmu | ptmgWRCWmu | ptmgWRCWmu | [
"~Kabir_Ahuja1",
"~Melanie_Sclar1",
"~Yulia_Tsvetkov1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8e9100661069abe51439f185fa13b0680bdf9b03.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"narrative understanding",
"reasoning",
"synthetic data generation",
"test time scaling",
"evaluation",
"natural 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{
ahuja2025finding,
title={Finding Flawed Fictions: Evaluating Complex Reasoning in Language Models via Plot Hole Detection},
author={Kabir Ahuja and Melanie Sclar and Yulia Tsvetkov},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=ptmgWRCWmu}
} | ahuja|finding_flawed_fictions_evaluating_complex_reasoning_in_language_models_via_plot_hole_detection | null | null | null | null | null | |
CoLa: Learning to Interactively Collaborate with Large Language Models | CoLa is an interactive learning framework to effectively collaborate with LLMs. | LLMs' remarkable ability to tackle a wide range of language tasks opened new opportunities for collaborative human-AI problem solving. LLMs can amplify human capabilities by applying their intuitions and reasoning strategies at scale. We explore whether human guides can be simulated, by generalizing from human demonst... | [
"Abhishek Sharma",
"Dan Goldwasser"
] | https://openreview.net/forum?id=pm9ykfhknK | pm9ykfhknK | pm9ykfhknK | [
"~Abhishek_Sharma7",
"~Dan_Goldwasser1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/885ff46bdcec539c57c36453e0c7e0f62ccff856.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Human Simulation",
"Interactive Learning",
"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{
sharma2025cola,
title={CoLa: Learning to Interactively Collaborate with Large Language Models},
author={Abhishek Sharma and Dan Goldwasser},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=pm9ykfhknK}
} | sharma|cola_learning_to_interactively_collaborate_with_large_language_models | null | null | null | null | null | |
Traceable and Explainable Multimodal Large Language Models: An Information-Theoretic View | We introduce an information-theoretic framework that uses mutual information, a Concept Bottleneck, and an InfoNCE mechanism to explain how multimodal models align and integrate visual and textual inputs. | Existing multimodal large language models (MLLMs) often lack traceable and explainable mechanisms for visual-textual alignment, making it challenging to understand how textual instructions shape multimodal representations. To address this shortcoming, we propose an information-theoretic framework that clarifies how MLL... | [
"Zihan Huang",
"Junda Wu",
"Rohan Surana",
"Raghav Jain",
"Tong Yu",
"Raghavendra Addanki",
"David Arbour",
"Sungchul Kim",
"Julian McAuley"
] | https://openreview.net/forum?id=pQm66IPmeE | pQm66IPmeE | pQm66IPmeE | [
"~Zihan_Huang1",
"~Junda_Wu1",
"~Rohan_Surana1",
"~Raghav_Jain1",
"~Tong_Yu3",
"~Raghavendra_Addanki1",
"~David_Arbour1",
"~Sungchul_Kim1",
"~Julian_McAuley1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8898dfdc9f6fbb8ae39d5dae4cef8545d2219ee3.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"multimodal LLM",
"information theory"
] | 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{
huang2025traceable,
title={Traceable and Explainable Multimodal Large Language Models: An Information-Theoretic View},
author={Zihan Huang and Junda Wu and Rohan Surana and Raghav Jain and Tong Yu and Raghavendra Addanki and David Arbour and Sungchul Kim and Julian McAuley},
booktitle={Second Conference... | huang|traceable_and_explainable_multimodal_large_language_models_an_informationtheoretic_view | null | null | null | null | null | |
Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topology | A framework quantifies uncertainty in LLM explanations through a formal reasoning topology perspective. | Understanding the uncertainty in large language model (LLM) explanations is important for evaluating their faithfulness and reasoning consistency, thus providing insights into the reliability of LLM's output. In this work, we propose a novel framework that quantifies uncertainty in LLM explanations through a formal rea... | [
"Longchao Da",
"Xiaoou Liu",
"Jiaxin Dai",
"Lu Cheng",
"Yaqing Wang",
"Hua Wei"
] | https://openreview.net/forum?id=p4wZfBFgyI | p4wZfBFgyI | p4wZfBFgyI | [
"~Longchao_Da1",
"~Xiaoou_Liu1",
"~Jiaxin_Dai2",
"~Lu_Cheng2",
"~Yaqing_Wang1",
"~Hua_Wei1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/f25b28f902394e53663073bcf82bb73491d92d95.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Uncertainty Quantification",
"LLM Explanations",
"Graph Mining"
] | 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{
da2025understanding,
title={Understanding the Uncertainty of {LLM} Explanations: A Perspective Based on Reasoning Topology},
author={Longchao Da and Xiaoou Liu and Jiaxin Dai and Lu Cheng and Yaqing Wang and Hua Wei},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openrevi... | da|understanding_the_uncertainty_of_llm_explanations_a_perspective_based_on_reasoning_topology | null | null | null | null | null | |
PrefPalette: Personalized Preference Modeling with Latent Attributes | PrefPalette models human preferences through interpretable latent attributes and community-specific weightings, outperforming GPT-4o by 46.6% on 45 Reddit communities/ | Personalizing AI systems requires understanding not just what users prefer, but the reasons that underlie those preferences—yet current preference models typically treat human judgment as a black box. We introduce PrefPalette, a framework that decomposes preferences into attribute dimensions and tailors its preference ... | [
"Shuyue Stella Li",
"Melanie Sclar",
"Hunter Lang",
"Ansong Ni",
"Jacqueline He",
"Puxin Xu",
"Andrew Cohen",
"Chan Young Park",
"Yulia Tsvetkov",
"Asli Celikyilmaz"
] | https://openreview.net/forum?id=p4ujQsKmPV | p4ujQsKmPV | p4ujQsKmPV | [
"~Shuyue_Stella_Li1",
"~Melanie_Sclar1",
"~Hunter_Lang1",
"~Ansong_Ni1",
"~Jacqueline_He1",
"~Puxin_Xu1",
"~Andrew_Cohen4",
"~Chan_Young_Park1",
"~Yulia_Tsvetkov1",
"~Asli_Celikyilmaz1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8de71e24767ae7de52d4c6da79f3c07ff1368f62.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Social Reasoning",
"Preference Modeling",
"Explainability"
] | 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{
li2025prefpalette,
title={PrefPalette: Personalized Preference Modeling with Latent Attributes},
author={Shuyue Stella Li and Melanie Sclar and Hunter Lang and Ansong Ni and Jacqueline He and Puxin Xu and Andrew Cohen and Chan Young Park and Yulia Tsvetkov and Asli Celikyilmaz},
booktitle={Second Confer... | li|prefpalette_personalized_preference_modeling_with_latent_attributes | null | null | null | null | null | |
LLMs as Research Tools: A Large Scale Survey of Researchers’ Usage and Perceptions | A large-scale survey of 816 researchers to study usage of LLMs in scientific research and the perception of such usage. | The rise of large language models (LLMs) has led many researchers to consider their usage for scientific work. Some have found benefits using LLMs to augment or automate aspects of their research pipeline, while others have urged caution due to risks and ethical concerns. Yet little work has sought to quantify and char... | [
"Zhehui Liao",
"Maria Antoniak",
"Inyoung Cheong",
"Evie Yu-Yen Cheng",
"Ai-Heng Lee",
"Kyle Lo",
"Joseph Chee Chang",
"Amy X Zhang"
] | https://openreview.net/forum?id=p0BwJk3R1p | p0BwJk3R1p | p0BwJk3R1p | [
"~Zhehui_Liao1",
"~Maria_Antoniak1",
"~Inyoung_Cheong1",
"~Evie_Yu-Yen_Cheng1",
"~Ai-Heng_Lee1",
"~Kyle_Lo1",
"~Joseph_Chee_Chang1",
"~Amy_X_Zhang1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/8fa13ec1b57aa5223febb7bcf9bfb12d49e14139.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"survey",
"large language model",
"research",
"societal impact"
] | 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{
liao2025llms,
title={{LLM}s as Research Tools: A Large Scale Survey of Researchers{\textquoteright} Usage and Perceptions},
author={Zhehui Liao and Maria Antoniak and Inyoung Cheong and Evie Yu-Yen Cheng and Ai-Heng Lee and Kyle Lo and Joseph Chee Chang and Amy X Zhang},
booktitle={Second Conference on ... | liao|llms_as_research_tools_a_large_scale_survey_of_researchers_usage_and_perceptions | /attachment/27da1dfac11a3cf6ed57dad4725449633edef625.zip | null | null | null | null | |
Vision-Language Models Are Not Pragmatically Competent in Referring Expression Generation | We show significant pragmatic deficiencies in current VLMs when faced with referring expression generation compared to humans, as they violate Gricean maxims. | Referring Expression Generation (REG) is a core task for evaluating the pragmatic competence of vision-language systems, requiring not only accurate semantic grounding but also adherence to principles of cooperative communication. However, current evaluations of vision-language models (VLMs) often overlook the pragmati... | [
"Ziqiao Ma",
"Jing Ding",
"Xuejun Zhang",
"Dezhi Luo",
"Jiahe Ding",
"Sihan Xu",
"Yuchen Huang",
"Run Peng",
"Joyce Chai"
] | https://openreview.net/forum?id=oj3ETSitjb | oj3ETSitjb | oj3ETSitjb | [
"~Ziqiao_Ma1",
"~Jing_Ding3",
"~Xuejun_Zhang4",
"~Dezhi_Luo1",
"~Jiahe_Ding1",
"~Sihan_Xu2",
"~Yuchen_Huang5",
"~Run_Peng1",
"~Joyce_Chai2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/572f9a40475cf207d0a6d41ebdd24de410b70bde.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Vision-Language Models",
"Pragmatics",
"Referring Expression 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{
ma2025visionlanguage,
title={Vision-Language Models Are Not Pragmatically Competent in Referring Expression Generation},
author={Ziqiao Ma and Jing Ding and Xuejun Zhang and Dezhi Luo and Jiahe Ding and Sihan Xu and Yuchen Huang and Run Peng and Joyce Chai},
booktitle={Second Conference on Language Mode... | ma|visionlanguage_models_are_not_pragmatically_competent_in_referring_expression_generation | null | null | null | null | null | |
SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation | This paper introduces a novel multi-stage prune-and-distill framework that efficiently compresses Phi-MoE 3.5 into compact 7.6B and 3.8B parameter models that significantly outperform similarly-sized alternatives. | The Mixture of Experts (MoE) architecture has emerged as a powerful paradigm for scaling large language models (LLMs) while maintaining inference efficiency. However, their substantial memory requirements make them prohibitively expensive to fine-tune or deploy in resource-constrained environments. To address this chal... | [
"Zichong Li",
"Chen Liang",
"Zixuan Zhang",
"Ilgee Hong",
"Young Jin Kim",
"Weizhu Chen",
"Tuo Zhao"
] | https://openreview.net/forum?id=oaCUsn391F | oaCUsn391F | oaCUsn391F | [
"~Zichong_Li2",
"~Chen_Liang3",
"~Zixuan_Zhang5",
"~Ilgee_Hong1",
"~Young_Jin_Kim1",
"~Weizhu_Chen1",
"~Tuo_Zhao2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/55e9e80f612fc74e9c3e47b1eafd56d35879cd4e.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Model",
"Mixture of Experts",
"Structured Pruning",
"Knowledge Distillation"
] | 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{
li2025slimmoe,
title={SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation},
author={Zichong Li and Chen Liang and Zixuan Zhang and Ilgee Hong and Young Jin Kim and Weizhu Chen and Tuo Zhao},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https:... | li|slimmoe_structured_compression_of_large_moe_models_via_expert_slimming_and_distillation | null | null | null | null | null | |
The Devil is in the EOS: Sequence Training for Detailed Image Captioning | Encourging detailed image captioning through end of sequence token debaising | Despite significant advances in vision-language models (VLMs), image captioning often suffers from a lack of detail, with base models producing short, generic captions. This limitation persists even though VLMs are equipped with strong vision and language backbones. While supervised data and complex reward functions ha... | [
"Abdelrahman Mohamed",
"Yova Kementchedjhieva"
] | https://openreview.net/forum?id=oSub7DiyjL | oSub7DiyjL | oSub7DiyjL | [
"~Abdelrahman_Mohamed3",
"~Yova_Kementchedjhieva1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/b764b38e67af5bc5f0ebf05ae0f332177a5f3d53.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Detailed image captioning; sequence training; reinforcement learning; vision langauge 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{
mohamed2025the,
title={The Devil is in the {EOS}: Sequence Training for Detailed Image Captioning},
author={Abdelrahman Mohamed and Yova Kementchedjhieva},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=oSub7DiyjL}
} | mohamed|the_devil_is_in_the_eos_sequence_training_for_detailed_image_captioning | null | null | null | null | null | |
Boundless Byte Pair Encoding: Breaking the Pre-tokenization Barrier | We propose an extension to BPE that allows pretokens to merge into superwords, leading to a more uniform token distribution and better compression. | Pre-tokenization, the initial step in many modern tokenization pipelines, segments text into smaller units called pretokens, typically splitting on whitespace and punctuation. While this process encourages having full, individual words as tokens, it introduces a fundamental limitation in most tokenization algorithms su... | [
"Craig W Schmidt",
"Varshini Reddy",
"Chris Tanner",
"Yuval Pinter"
] | https://openreview.net/forum?id=oPAjXGV8qQ | oPAjXGV8qQ | oPAjXGV8qQ | [
"~Craig_W_Schmidt1",
"~Varshini_Reddy2",
"~Chris_Tanner1",
"~Yuval_Pinter1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/e812cb86f37b3a79329043b3b6b9ab1bc1033cfd.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"tokenization",
"Byte Pair Encoding",
"BPE",
"subword tokenization"
] | 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{
schmidt2025boundless,
title={Boundless Byte Pair Encoding: Breaking the Pre-tokenization Barrier},
author={Craig W Schmidt and Varshini Reddy and Chris Tanner and Yuval Pinter},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=oPAjXGV8qQ}
} | schmidt|boundless_byte_pair_encoding_breaking_the_pretokenization_barrier | null | null | null | null | null | |
Layerwise Importance Analysis of Feed-Forward Networks in Transformer-based Language Models | FFNs in 70% of the consecutive middle layers of Transformer-based LM contribute more to model performance than other layers. | This study investigates the layerwise importance of feed-forward networks (FFNs) in transformer-based language models during pretraining.
We introduce an experimental approach that, while maintaining the total parameter count, increases the FFN dimensions in some layers and completely removes the FFNs from other layers... | [
"Wataru Ikeda",
"Kazuki Yano",
"Ryosuke Takahashi",
"Jaesung Lee",
"KeigoShibata",
"Jun Suzuki"
] | https://openreview.net/forum?id=oP3b5YBFoP | oP3b5YBFoP | oP3b5YBFoP | [
"~Wataru_Ikeda2",
"~Kazuki_Yano1",
"~Ryosuke_Takahashi2",
"~Jaesung_Lee3",
"~KeigoShibata1",
"~Jun_Suzuki1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/061c656981c2fe4b6df90b654e9d2f6685a699ca.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Feed-Forward Networks",
"Model Architecture",
"Knowledge Representation",
"Pre-training"
] | 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{
ikeda2025layerwise,
title={Layerwise Importance Analysis of Feed-Forward Networks in Transformer-based Language Models},
author={Wataru Ikeda and Kazuki Yano and Ryosuke Takahashi and Jaesung Lee and KeigoShibata and Jun Suzuki},
booktitle={Second Conference on Language Modeling},
year={2025},
url={http... | ikeda|layerwise_importance_analysis_of_feedforward_networks_in_transformerbased_language_models | null | null | null | null | null | |
Synthetic Data Generation and Multi-Step Reinforcement Learning for Reasoning and Tool Use | We propose a synthetic data generation and RL methodology for multi-step reasoning and tool use. | Reinforcement learning has been shown to improve the performance of large language models. However, traditional approaches like RLHF or RLAIF treat the problem as single-step. As focus is shifting towards solving more complex reasoning and agentic tasks, language models must take multiple steps of text generation, reas... | [
"Anna Goldie",
"Azalia Mirhoseini",
"Hao Zhou",
"Irene Cai",
"Christopher D Manning"
] | https://openreview.net/forum?id=oN9STRYQVa | oN9STRYQVa | oN9STRYQVa | [
"~Anna_Goldie2",
"~Azalia_Mirhoseini3",
"~Hao_Zhou46",
"~Irene_Cai1",
"~Christopher_D_Manning1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/474b99204f9524eb1382562f7c89a5910f85b284.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Large Language Models",
"Reinforcement Learning",
"Multi-Step Reasoning",
"Tool Use",
"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{
goldie2025synthetic,
title={Synthetic Data Generation and Multi-Step Reinforcement Learning for Reasoning and Tool Use},
author={Anna Goldie and Azalia Mirhoseini and Hao Zhou and Irene Cai and Christopher D Manning},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openrevi... | goldie|synthetic_data_generation_and_multistep_reinforcement_learning_for_reasoning_and_tool_use | null | null | null | null | null | |
Rhapsody: A Dataset for Highlight Detection in Podcasts | We present a dataset of 13K podcast episodes paired with segment-level highlight scores. | Podcasts have become daily companions for half a billion users. Given the enormous amount of podcast content available, highlights provide a valuable signal that helps viewers get the gist of an episode and decide if they want to invest in listening to it in its entirety. However, identifying highlights automatically i... | [
"Younghan Park",
"Anuj Diwan",
"David Harwath",
"Eunsol Choi"
] | https://openreview.net/forum?id=oKdVFxngy1 | oKdVFxngy1 | oKdVFxngy1 | [
"~Younghan_Park1",
"~Anuj_Diwan1",
"~David_Harwath1",
"~Eunsol_Choi1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/4a008730e477e28f83e5e20da6a289def694aacc.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"podcast highlight detection",
"long-context reasoning",
"spoken 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{
park2025rhapsody,
title={Rhapsody: A Dataset for Highlight Detection in Podcasts},
author={Younghan Park and Anuj Diwan and David Harwath and Eunsol Choi},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=oKdVFxngy1}
} | park|rhapsody_a_dataset_for_highlight_detection_in_podcasts | null | null | null | null | null | |
ThoughtTerminator: Benchmarking, Calibrating, and Mitigating Overthinking in Reasoning Models | We evaluate the relationship between problem difficulty and token cost in reasoning models, benchmark how efficiently different models allocate tokens, and introduce a simple training-free decoding method to reduce overthinking, Thought Terminator. | Reasoning models have demonstrated impressive performance on difficult tasks that traditional language models struggle at. However, many are plagued with the problem of overthinking---generating large amounts of unnecessary tokens which don't improve accuracy on a question. We introduce approximate measures of problem-... | [
"Xiao Pu",
"Michael Saxon",
"Wenyue Hua",
"William Yang Wang"
] | https://openreview.net/forum?id=oHR862dpMC | oHR862dpMC | oHR862dpMC | [
"~Xiao_Pu2",
"~Michael_Saxon1",
"~Wenyue_Hua1",
"~William_Yang_Wang2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/be760f06990b1cc580adbc28bf7e09c23cabe7a2.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"reasoning model",
"overthinking",
"decoding",
"tool use",
"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{
pu2025thoughtterminator,
title={ThoughtTerminator: Benchmarking, Calibrating, and Mitigating Overthinking in Reasoning Models},
author={Xiao Pu and Michael Saxon and Wenyue Hua and William Yang Wang},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=o... | pu|thoughtterminator_benchmarking_calibrating_and_mitigating_overthinking_in_reasoning_models | null | null | null | null | null | |
Plato: Plan to Efficient Decode for Large Language Model Inference | Plan to exploit parallelism structure to break the autoregressive nature of LLM inference. | Large language models (LLMs) have achieved remarkable success in natural language tasks, but their inference incurs substantial computational and memory overhead.
To improve efficiency, parallel decoding methods like Skeleton-of-Thought (SoT) decompose prompts into sub-problems for concurrent processing. However, these... | [
"Shuowei Jin",
"Xueshen Liu",
"Yongji Wu",
"Haizhong Zheng",
"Qingzhao Zhang",
"Atul Prakash",
"Matthew Lentz",
"Danyang Zhuo",
"Feng Qian",
"Zhuoqing Mao"
] | https://openreview.net/forum?id=oGO0fNVWrN | oGO0fNVWrN | oGO0fNVWrN | [
"~Shuowei_Jin1",
"~Xueshen_Liu1",
"~Yongji_Wu1",
"~Haizhong_Zheng1",
"~Qingzhao_Zhang1",
"~Atul_Prakash1",
"~Matthew_Lentz1",
"~Danyang_Zhuo1",
"~Feng_Qian4",
"~Zhuoqing_Mao1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/14b0fc4f8d7204c3034c61a920be7e0720064fda.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Efficient LLM Inference"
] | 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{
jin2025plato,
title={Plato: Plan to Efficient Decode for Large Language Model Inference},
author={Shuowei Jin and Xueshen Liu and Yongji Wu and Haizhong Zheng and Qingzhao Zhang and Atul Prakash and Matthew Lentz and Danyang Zhuo and Feng Qian and Zhuoqing Mao},
booktitle={Second Conference on Language ... | jin|plato_plan_to_efficient_decode_for_large_language_model_inference | null | null | null | null | null | |
Probing Syntax in Large Language Models: Successes and Remaining Challenges | This work evaluates syntactic representations in LLMs using structural probes. We assess these probes across three benchmarks, revealing that their accuracy is compromised by linear distance and syntactic depth, yet remains invariant to surprisal. | The syntactic structures of sentences can be readily read-out from the activations of large language models (LLMs). However, the ``structural probes'' that have been developed to reveal this phenomenon are typically evaluated on an indiscriminate set of sentences. Consequently, it remains unclear whether structural and... | [
"Pablo J. Diego Simon",
"Emmanuel Chemla",
"Jean-Remi King",
"Yair Lakretz"
] | https://openreview.net/forum?id=nrZysNmJ0n | nrZysNmJ0n | nrZysNmJ0n | [
"~Pablo_J._Diego_Simon1",
"~Emmanuel_Chemla1",
"~Jean-Remi_King1",
"~Yair_Lakretz2"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c6a94b429ad0d683d6dff35df27378dfcab59ab1.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"Syntax",
"LLMs",
"Probing",
"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{
simon2025probing,
title={Probing Syntax in Large Language Models: Successes and Remaining Challenges},
author={Pablo J. Diego Simon and Emmanuel Chemla and Jean-Remi King and Yair Lakretz},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openreview.net/forum?id=nrZysNmJ0n}
... | simon|probing_syntax_in_large_language_models_successes_and_remaining_challenges | null | null | null | null | null | |
CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing | A novel Collaborative Inference with Token-lEvel Routing (CITER) framework that introduces a token-level routing mechanism, enabling efficient collaboration between small and large language models (SLMs & LLMs). | Large language models have achieved remarkable success in various tasks but suffer from high computational costs during inference, limiting their deployment in resource-constrained applications. To address this issue, we propose a novel Collaborative Inference with Token-lEvel Routing (CITER) framework that enables eff... | [
"Wenhao Zheng",
"Yixiao Chen",
"Weitong Zhang",
"Souvik Kundu",
"Yun Li",
"Zhengzhong Liu",
"Eric P. Xing",
"Hongyi Wang",
"Huaxiu Yao"
] | https://openreview.net/forum?id=nqX9UYW9Af | nqX9UYW9Af | nqX9UYW9Af | [
"~Wenhao_Zheng4",
"~Yixiao_Chen2",
"~Weitong_Zhang2",
"~Souvik_Kundu2",
"~Yun_Li7",
"~Zhengzhong_Liu1",
"~Eric_Xing1",
"~Hongyi_Wang1",
"~Huaxiu_Yao1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/44adc116c02c1f30777bdd97bc65accd40cb593a.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"collaborative inference",
"efficient inference",
"token-level routing",
"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{
zheng2025citer,
title={{CITER}: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing},
author={Wenhao Zheng and Yixiao Chen and Weitong Zhang and Souvik Kundu and Yun Li and Zhengzhong Liu and Eric P. Xing and Hongyi Wang and Huaxiu Yao},
booktitle={Second Confere... | zheng|citer_collaborative_inference_for_efficient_large_language_model_decoding_with_tokenlevel_routing | null | null | null | null | null | |
Text Speaks Louder than Vision: ASCII Art Reveals Textual Biases in Vision-Language Models | Multimodal models struggle with adversarial ASCII art images, revealing limitations in information alignment. | Vision-language models (VLMs) have advanced rapidly in processing multimodal information, but their ability to reconcile conflicting signals across modalities remains underexplored. This study investigates how VLMs process ASCII art, a unique medium where textual elements collectively form visual patterns, potentially ... | [
"Zhaochen Wang",
"Bryan Hooi",
"Yiwei Wang",
"Ming-Hsuan Yang",
"Zi Huang",
"Yujun Cai"
] | https://openreview.net/forum?id=naEyNVTLsh | naEyNVTLsh | naEyNVTLsh | [
"~Zhaochen_Wang1",
"~Bryan_Hooi1",
"~Yiwei_Wang2",
"~Ming-Hsuan_Yang1",
"~Zi_Huang1",
"~Yujun_Cai1"
] | {
"value": "COLM 2025"
} | {
"value": "colmweb.org/COLM/2025/Conference"
} | {
"value": "/pdf/c8c8412cde77ce8cdb46ae02a22e6dfe87928ea8.pdf"
} | conference | colmweb.org/COLM/2025/Conference | 2,025 | COLM | [
"vision language model",
"ASCII art",
"sentiment analysis"
] | 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{
wang2025text,
title={Text Speaks Louder than Vision: {ASCII} Art Reveals Textual Biases in Vision-Language Models},
author={Zhaochen Wang and Bryan Hooi and Yiwei Wang and Ming-Hsuan Yang and Zi Huang and Yujun Cai},
booktitle={Second Conference on Language Modeling},
year={2025},
url={https://openrevie... | wang|text_speaks_louder_than_vision_ascii_art_reveals_textual_biases_in_visionlanguage_models | null | null | null | null | null |
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