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Know When to Stop, Where to Restart: Accelerating Multi-Turn Agentic On-Policy Distillation

Gui, Zhiyu et al.
arXiv (OAI Expanded) · Papers
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computation-and-languagemachine-learning
On-policy distillation (OPD) has become a standard approach for transferring capabilities from large teachers to compact students. Its cost, however, is dominated by autoregressive student rollouts and scales poorly in multi-turn agentic settings. Existing acceleration methods truncate or relocate t
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