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cs.CL2026
Bootstrapping Exploration with Group-Level Natural Language Feedback in Reinforcement Learning
Lei Huang, Xiang Cheng, Chenxiao Zhao +6
Large language models (LLMs) typically receive diverse natural language (NL) feedback through interaction with the environment. However, current reinforcement learning (RL) algorit…
cs.CL2025
Retrieval-Augmented Generation with Hierarchical Knowledge
Haoyu Huang, Yongfeng Huang, Junjie Yang +5
Graph-based Retrieval-Augmented Generation (RAG) methods have significantly enhanced the performance of large language models (LLMs) in domain-specific tasks. However, existing RAG…
cs.CL2025
Think When You Need: Self-Adaptive Chain-of-Thought Learning
Junjie Yang, Ke Lin, Xing Yu
Chain of Thought (CoT) reasoning enhances language models' performance but often leads to inefficient "overthinking" on simple problems. We identify that existing approaches direct…