What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents

In three linesSERL, a selective environment-reweighted learning framework, improves multi-turn LLM agent training by leveraging granular environmental feedback (error messages, page changes, reference trajectories). On ALFWorld and WebShop, SERL achieves 90.0% and 80.1% success rates, outperforming existing RL and distillation baselines.

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