作者位次 #3/5ACL 2026Poster· Natural Language Processing
AAPO : Enhancing the Reasoning Capabilities of LLM s with Advantage Margin
Jian Xiong · Jingbo Zhou · Jingyong Ye · Qiang Huang · Dejing Dou
摘要
Reinforcement learning (RL) has emerged as an effective approach for enhancing the reasoning capabilities of large language models (LLMs), especially in scenarios where supervised fine-tuning (SFT) falls short due to limited chain-of-thought (CoT) data. Among RL-based post-training methods, group...