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Paper · arXiv

Many Steps into One: Reasoning Contraction and the Limits of Safe Memory Reuse for LLM Agents

Thought templates, skill libraries, agent memories and caches turn many reasoning steps into one. We call this reasoning contraction. A contracted memory saves reasoning steps and errors until its facts change, then quietly answers wrong. Most systems trust memories by counting successes and failures. We prove that such counters are badly tuned change detectors: a symmetric counter notices a partial change only after a power of its false-alarm horizon, and an unclipped one may never notice it. On five LLMs answering multi-hop questions over edited facts, ExpeL- and ACE-style counters serve 7.0-13.5x more stale answers than certified memories given the same information, and on code tasks w...

AuthorsJianghong Zhou, Hao Rong, Chen Lin et al.
Primary categorycs.CL
Published13 October 2026
Last updated at source13 October 2026
cs.CLcs.AI
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