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DENSE: Distilling Agent Trajectories into Evidence-Grounded Shortcut Trees for Self-Refinement

arXiv:2609.21423v1 Announce Type: new Abstract: Online agent deployments produce abundant execution traces, while task-specific verification and expert annotation are costly to scale. We study how to distill these traces into reusable feedback without post-hoc outcome labels, drawing on their evide…

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  1. 2026-09-21 04:00 · arXiv cs.AI
    DENSE: Distilling Agent Trajectories into Evidence-Grounded Shortcut Trees for Self-Refinement

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