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News/Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents
arxiv
PublishedJune 29, 2026 at 4:00 AM
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Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents

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arXiv:2606.27472v1 Announce Type: cross Abstract: Large language model (LLM) agents operate over long, multi-session interactions in which facts change: a user moves, a price updates, a plan is revised. Acting correctly requires using the current value of a fact and discarding values that have been

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