4 papers · 1 filter
TTRSD: Test-Time Reinforcement Learning with Self-Distillation for Vision-Language Models
Shuning Wang, Zhiheng Wu, Xun Zhou +8
Test-time reinforcement learning enables vision-language models (VLMs) to adapt using unlabeled inputs. However, repeated sampling under fixed visual conditions can reinforce share…
See More, Think Deeper: Query-Expanded Visual Evidence and Answer-Clue Guided Reflection for Long Video Understanding
Shuning Wang, Zhiheng Wu, YiNuo Lu +6
Recent advances in Video Large Language Models (Video-LLMs) have enabled performance on long-video understanding tasks. However, existing methods still face two key limitations: ev…
Flow-Factory: A Unified Framework for Reinforcement Learning in Flow-Matching Models
Bowen Ping, Chengyou Jia, Minnan Luo +2
Reinforcement learning has emerged as a promising paradigm for aligning diffusion and flow-matching models with human preferences, yet practitioners face fragmented codebases, mode…
GDEPO: Group Dual-dynamic and Equal-right Advantage Policy Optimization for Sample-Efficient Reinforcement Learning
Zhengqing Yan, Xinyang Liu, Yi Zhang +7
Automated Theorem Proving (ATP) is a fundamental AI challenge, requiring machine-verifiable proofs in formal languages like Lean to evaluate reasoning. Reinforcement Learning (RL),…