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TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training

Zhou, Yuhang et al.
arXiv (All) · Papers
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computation-and-language
On-policy distillation (OPD) trains a student policy by matching a stronger teacher on the student's own trajectories, offering a promising framework for language agent training. However, its application to long-horizon agentic tasks remains insufficiently explored. We identify two key inefficiencie
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