arxivcs.CLcs.AIcs.LG2026-06-25
Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents
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 Acting correctly requires using the current value of a fact and discarding values that have been superseded. We isolate this ab…