The Right Memory in the Wrong Context: Verifying Retrieval Admissibility in Long-Term Agent Memory
cs.AI, cs.IR, cs.MA
Submitted: 2026-10-05
Updated: 2026-10-05
Comments: 26 pages. Accepted at the NeurIPS 2026 Workshop "Who Verifies the Agents? Toward Reliable Agent Development". Code: https://github.com/ziwang11112/right-memory-wrong-context
Code: https://github.com/ziwang11112/right-memory-wrong-context
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- SD-RAG: A Prompt-Injection-Resilient Framework for Selective Disclosure in Retrieval-Augmented Generation
- STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?
- Selection Integrity for LLM Graph Memory: An Accumulability Criterion for Information-Flow-Blind Retrieval
- MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations
- MRMS: A Multi-Resolution Memory Substrate for Long-Lived AI Agents
- MemAudit: Auditing Long-Term Agent Memory via Hidden User-State Recovery
- Governed Shared Memory for Multi-Agent LLM Systems
- GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents
- Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control
- A-TMA: Decoupling State-Aware Memory Failures in Long-Term Agent Memory
- MemConflict: Evaluating Long-Term Memory Systems Under Memory Conflicts
- MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows
- LongMemEval-V2: Evaluating Long-Term Agent Memory Toward Experienced Colleagues
- RaMem: Contextual Reinstatement for Long-term Agentic Memory
- Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory
- Beyond Similarity: Trustworthy Memory Search for Personal AI Agents
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