arXiv 2610.27406 · cs.AI · 2026-10-19
More Memory, Worse Agents: Error Reproduction and Anti-Persistence in LLM Agents
Ruhan Wang, Kishan Panaganti, Dongruo Zhou
Indiana University Bloomington
In latest · #390 Added on 2026-10-26
One-line takeaway
Agents that store abstracted rules and skills in memory can suffer "error reproduction": faulty abstractions shape new trajectories that are re-abstracted into the same errors, making them persist beyond direct reuse.
论文指出智能体把经验抽象成规则和技能存进记忆时，错误会经「抽象、执行、再抽象」循环不断再生，称为错误复现，使错误比直接复用错误知识持续得更久。
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About this data
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