作者位次 #6/9ACL 2026Findings· Findings of ACL
E vo C o T : Overcoming the Exploration Bottleneck in Reinforcement Learning for LLM s
Huanyu Liu · Jia Li · Yihong Dong · Chang Yu · Taozhi Chen · Lecheng Wang · Yongding Tao · Bin Gu · Ge Li
摘要
Reinforcement learning with verifiable reward (RLVR) has become a promising paradigm for post-training large language models (LLMs) to improve their reasoning capability. However, when the rollout accuracy is low on hard problems, the reward becomes sparse, limiting learning efficiency and causin...