Targeting Pivotal Decisions for Credit Assignment in Agentic Reinforcement Learning
Group Relative Policy Optimization (GRPO) has become a promising approach for training large language model agents. However, its uniform assignment of trajectory-level advantages to all policy tokens fails to distinguish consequential decisions from less relevant ones, obscuring which intermediate decisions contributed...
Dongwon Jung, H. Ramesh, Yi-Fan Wang et al.
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