arxiv
PublishedOctober 19, 2026 at 4:00 AM
Self-Evolving Coding Agents via Harness-Policy Optimization
Publisher summary· verbatim
arXiv:2610.22791v1 Announce Type: cross Abstract: Large language model (LLM) agents have shown promising potential in coding tasks, and their performance is jointly determined by the policy model and the harness that mediates their interaction with the environment. Indeed, harness and policy are mut
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 Response10harxivLearning Transferable Latent User Preferences for Human-Aligned Decision Making10harxivRepair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents10harxivIndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD10hThe 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 ↗