AgentMemGate: Addressing Speculation Contamination in Conversational Assistant Memory
Conversational AI assistants with long-term memory extract facts from user messages into a store consulted in later conversations.
ProofPaper ↗
Key points
- Final-state memory benchmarks miss this error because they do not probe intermediate state and include few unresolved speculations.
- We present AgentMemGate, a write-time gate for profile-store memory that classifies extracted statements as speculation, completed event, correction, or other.
- We also contribute a dataset of multi-session conversations in which plans are confirmed, abandoned, or left unresolved.
- Our analysis identifies field matching as the main remaining bottleneck: realistic speculations often match no profile field and never reach the gate.
Sources (1)
- [1]AgentMemGate: Addressing Speculation Contamination in Conversational Assistant MemoryarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 6, 03:59 AM
Conversational AI assistants with long-term memory extract facts from user messages into a store consulted in later conversations.
Final-state memory benchmarks miss this error because they do not probe intermediate state and include few unresolved speculations.
Extractive summary: sentences quoted from the sources.