arxiv
PublishedOctober 21, 2026 at 4:00 AM
Self-Evolving Agents through Privileged Retrospective Distillation
Publisher summary· verbatim
arXiv:2610.27495v1 Announce Type: cross Abstract: Self-evolving agents aim to improve from their own experience rather than remain fixed after deployment, but naturally collected trajectories often lack ground-truth solutions or verifier-derived rewards. We introduce Retrospective Self-Distillation
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response7harxivLearning Transferable Latent User Preferences for Human-Aligned Decision Making7harxivRepair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents7harxivIndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD7hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗