作者位次 #3/6ACL 2026Poster· Natural Language Processing
Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling
Jiaxuan Wang · Yulan Hu · Wenjin Yang · Zheng Pan · Xin Li · Lan-Zhe Guo
摘要
In classical Reinforcement Learning from Human Feedback (RLHF), Reward Models (RMs) serve as the fundamental signal provider for model alignment. As Large Language Models evolve into agentic systems capable of autonomous tool invocation and complex reasoning, the paradigm of reward modeling faces...