Collection by 
Jul 19, 2025
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Discover the best community collections!
Collections including paper arxiv:2505.10475
Collection by 
Jun 28, 2025
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CoRAG: Collaborative Retrieval-Augmented Generation
Paper • 2504.01883 • Published • 9 -
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
Paper • 2504.08837 • Published • 44 -
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
Paper • 2504.10068 • Published • 30 -
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations
Paper • 2504.10481 • Published • 85
Collection by 
Aug 25, 2025
Collection by 
May 27, 2025
Collection by 
22 days ago
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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 29 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 15 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 50 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
Collection by 
Jun 26, 2025
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Parallel Scaling Law for Language Models
Paper • 2505.10475 • Published • 83 -
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective
Paper • 2505.15045 • Published • 56 -
Scaling Diffusion Transformers Efficiently via μP
Paper • 2505.15270 • Published • 35 -
Vision Transformers Don't Need Trained Registers
Paper • 2506.08010 • Published • 22
Collection by 
Mar 18
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CoLLM: A Large Language Model for Composed Image Retrieval
Paper • 2503.19910 • Published • 15 -
Parallel Scaling Law for Language Models
Paper • 2505.10475 • Published • 83 -
OLMoE: Open Mixture-of-Experts Language Models
Paper • 2409.02060 • Published • 80 -
Dynamic Chunking Diffusion Transformer
Paper • 2603.06351 • Published • 15
Collection by 
Nov 18, 2025
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The Curse of Depth in Large Language Models
Paper • 2502.05795 • Published • 40 -
Transformers without Normalization
Paper • 2503.10622 • Published • 172 -
Parallel Scaling Law for Language Models
Paper • 2505.10475 • Published • 83 -
Learning to Skip the Middle Layers of Transformers
Paper • 2506.21103 • Published • 18
Collection by 
Jan 26
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 53 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
Collection by 
Mar 18
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Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Paper • 2401.01335 • Published • 69 -
Lumiere: A Space-Time Diffusion Model for Video Generation
Paper • 2401.12945 • Published • 86 -
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU
Paper • 2403.06504 • Published • 56 -
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs
Paper • 2403.20041 • Published • 34
Collection by Jul 19, 2025
Collection by Jun 26, 2025
-
Parallel Scaling Law for Language Models
Paper • 2505.10475 • Published • 83 -
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective
Paper • 2505.15045 • Published • 56 -
Scaling Diffusion Transformers Efficiently via μP
Paper • 2505.15270 • Published • 35 -
Vision Transformers Don't Need Trained Registers
Paper • 2506.08010 • Published • 22
Collection by Jun 28, 2025
-
CoRAG: Collaborative Retrieval-Augmented Generation
Paper • 2504.01883 • Published • 9 -
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
Paper • 2504.08837 • Published • 44 -
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
Paper • 2504.10068 • Published • 30 -
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations
Paper • 2504.10481 • Published • 85
Collection by Mar 18
-
CoLLM: A Large Language Model for Composed Image Retrieval
Paper • 2503.19910 • Published • 15 -
Parallel Scaling Law for Language Models
Paper • 2505.10475 • Published • 83 -
OLMoE: Open Mixture-of-Experts Language Models
Paper • 2409.02060 • Published • 80 -
Dynamic Chunking Diffusion Transformer
Paper • 2603.06351 • Published • 15
Collection by Aug 25, 2025
Collection by Nov 18, 2025
-
The Curse of Depth in Large Language Models
Paper • 2502.05795 • Published • 40 -
Transformers without Normalization
Paper • 2503.10622 • Published • 172 -
Parallel Scaling Law for Language Models
Paper • 2505.10475 • Published • 83 -
Learning to Skip the Middle Layers of Transformers
Paper • 2506.21103 • Published • 18
Collection by May 27, 2025
Collection by Jan 26
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 53 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
Collection by 22 days ago
-
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 29 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 15 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 50 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
Collection by Mar 18
-
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Paper • 2401.01335 • Published • 69 -
Lumiere: A Space-Time Diffusion Model for Video Generation
Paper • 2401.12945 • Published • 86 -
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU
Paper • 2403.06504 • Published • 56 -
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs
Paper • 2403.20041 • Published • 34