-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 277 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 187 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 142 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97
Collections
Discover the best community collections!
Collections including paper arxiv:2505.19147
-
TabSTAR: A Foundation Tabular Model With Semantically Target-Aware Representations
Paper • 2505.18125 • Published • 112 -
On-Policy RL with Optimal Reward Baseline
Paper • 2505.23585 • Published • 14 -
Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software Engineering
Paper • 2505.23604 • Published • 23 -
Are Reasoning Models More Prone to Hallucination?
Paper • 2505.23646 • Published • 24
-
One-Minute Video Generation with Test-Time Training
Paper • 2504.05298 • Published • 110 -
MoCha: Towards Movie-Grade Talking Character Synthesis
Paper • 2503.23307 • Published • 138 -
Towards Understanding Camera Motions in Any Video
Paper • 2504.15376 • Published • 157 -
Antidistillation Sampling
Paper • 2504.13146 • Published • 59
-
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
Paper • 2411.04952 • Published • 30 -
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Paper • 2411.05005 • Published • 13 -
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
Paper • 2411.04075 • Published • 17 -
Self-Consistency Preference Optimization
Paper • 2411.04109 • Published • 19
-
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 300 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 303 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
-
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 • 43 -
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
-
LLMs + Persona-Plug = Personalized LLMs
Paper • 2409.11901 • Published • 35 -
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Paper • 2409.12183 • Published • 39 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13 -
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
Paper • 2410.00531 • Published • 34
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 277 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 187 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 142 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97
-
TabSTAR: A Foundation Tabular Model With Semantically Target-Aware Representations
Paper • 2505.18125 • Published • 112 -
On-Policy RL with Optimal Reward Baseline
Paper • 2505.23585 • Published • 14 -
Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software Engineering
Paper • 2505.23604 • Published • 23 -
Are Reasoning Models More Prone to Hallucination?
Paper • 2505.23646 • Published • 24
-
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 300 -
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Paper • 2504.10479 • Published • 303 -
What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models
Paper • 2503.24235 • Published • 54 -
Seedream 3.0 Technical Report
Paper • 2504.11346 • Published • 70
-
One-Minute Video Generation with Test-Time Training
Paper • 2504.05298 • Published • 110 -
MoCha: Towards Movie-Grade Talking Character Synthesis
Paper • 2503.23307 • Published • 138 -
Towards Understanding Camera Motions in Any Video
Paper • 2504.15376 • Published • 157 -
Antidistillation Sampling
Paper • 2504.13146 • Published • 59
-
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 • 43 -
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
-
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
Paper • 2411.04952 • Published • 30 -
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
Paper • 2411.05005 • Published • 13 -
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
Paper • 2411.04075 • Published • 17 -
Self-Consistency Preference Optimization
Paper • 2411.04109 • Published • 19
-
LLMs + Persona-Plug = Personalized LLMs
Paper • 2409.11901 • Published • 35 -
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Paper • 2409.12183 • Published • 39 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13 -
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
Paper • 2410.00531 • Published • 34