2 papers
cs.CL2026
Right Answer, Wrong Tokens: Tail-Aware Credit Calibration for RLVR
Xiuyi Lou, Zicheng Xu, Yu-Neng Chuang +4
Although reinforcement learning (RL) improves the reasoning capabilities of large language models (LLMs), GRPO-style methods can suffer from a positive-credit contamination failure…
cs.CL2026
Learning at the Right Pace: Adaptive Data Scheduling Improves LLM Reinforcement Learning
Zicheng Xu, Ruixuan Zhang, Yu-Neng Chuang +7
Large Language Models (LLMs) achieve remarkable reasoning capabilities through reinforcement learning (RL) post-training. However, existing RL post-training commonly relies on unif…