Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents
DGX agentarXiv: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 revise