一作ACL 2026Poster· Natural Language Processing
Reinforced Efficient Reasoning via Semantically Diverse Exploration
Ziqi Zhao · Zhaochun Ren · Jiahong Zou · Liu Yang · Zhiwei XU · Xuri Ge · Zhumin Chen · xinyu ma · Daiting Shi · Shuaiqiang Wang · Dawei Yin · Xin Xin
摘要
Reinforcement learning with verifiable rewards (RLVR) has proven effective in enhancing the reasoning of large language models (LLMs). Monte Carlo Tree Search (MCTS)-based extensions improve upon vanilla RLVR (e.g., GRPO) by providing tree-based reasoning rollouts that enable fine-grained and seg...