Mitigating Provenance-Role Collapse in Long-Term Agents via Typed Memory Representation 事件

Mitigating Provenance-Role Collapse in Long-Term Agents via Typed Memory Representation arXiv:2605.25869v1 Announce Type: new Abstract: Long-term memory is essential for persistent LLM agents, yet prevailing architectures store historical interactions as unstructured, flat text. This unconstrained storage induces provenance-role collapse, a critical failure mode where agents suffer from source-monitoring errors. To resolve this cognitive vulnerability at the architectural level, we propose MemI