AI RESEARCH
Hindsight Credit Assignment for Long-Horizon LLM Agents
arXiv CS.AI
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ArXi:2603.08754v1 Announce Type: cross Large Language Model (LLM) agents often face significant credit assignment challenges in long-horizon, multi-step tasks due to sparse rewards. Existing value-free methods, such as Group Relative Policy Optimization (GRPO), encounter two fundamental bottlenecks: inaccurate step-level Q-value estimation and misaligned value baselines for intermediate states. To address these limitations, we