4 papers
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
Guanhua Huang, Tingqiang Xu, Mingze Wang +7
Reinforcement Learning with Verifiable Rewards (RLVR) has propelled Large Language Models in complex reasoning, yet its scalability is often hindered by a training bottleneck where…
Reinforcement Learning on Pre-Training Data
Siheng Li, Kejiao Li, Zenan Xu +33
The growing disparity between the exponential scaling of computational resources and the finite growth of high-quality text data now constrains conventional scaling approaches for…
Adaptive Termination for Multi-round Parallel Reasoning: An Universal Semantic Entropy-Guided Framework
Zenan Xu, Zexuan Qiu, Guanhua Huang +9
Recent advances in large language models (LLMs) have accelerated progress toward artificial general intelligence, with inference-time scaling emerging as a key technique. Contempor…
RePO: Replay-Enhanced Policy Optimization
Siheng Li, Zhanhui Zhou, Wai Lam +2
Reinforcement learning (RL) is vital for optimizing large language models (LLMs). Recent Group Relative Policy Optimization (GRPO) estimates advantages using multiple on-policy out…