Exploring Reasoning Reward Model for Agents
By: Kaixuan Fan, Kaituo Feng, Manyuan Zhang, Tianshuo Peng, Zhixun Li, Yilei Jiang, Shuang Chen, Peng Pei, Xunliang Cai, Xiangyu Yue
Published: 2026-01-30
View on arXiv →#cs.AI
Abstract
This paper focuses on developing and exploring a reasoning reward model designed to improve the capabilities of AI agents. It likely investigates how to effectively train agents by providing rewards that are aligned with complex reasoning processes, leading to more intelligent and robust agent behaviors in various applications.