Matched-Context Group Policy Optimization for LLM Agent Training
Training long-horizon language model agents requires assigning credit to intermediate decisions from sparse terminal feedback. Within a finite group of sibling rollouts, useful action comparisons depend on their context, evidence for both alternatives, and how that evidence enters learning. We propose Matched-Context G...
Chen-Xu Zhang, Yao-Rui Shi, Wen-Long Zhang et al.
· 0 citations