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Matching papers

False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents

167 upvotes · 30 SEP 2026 · Meijia Chen, Hao Li, Zheng Lu et al.

This paper identifies a problem in self-evolving search agents where the proposer and solver agree on errors, leading to improved internal reward without better external performance. Practitioners might care about this issue to develop more reliable search agents that can learn from their mistakes.

self-evolving search agentscontinual learningpseudo-labelsverificationcross-fittingsearch optimization