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RoutePrism: Tracing Construction Order Effects in Agent Memory

arXiv 2609.34160 ↗First posted 28 Sep 2026cs.AIcited by 0

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Abstract (arXiv)

Processing the same records in a different order can discard different evidence, yet endpoint accuracy alone cannot reveal what changed or whether it mattered. We introduce RoutePrism, a diagnostic protocol that builds memory twice from the same source pool in two processing orders, then traces which sources, compiled contexts, and answers differ. Because record content, timestamps, policy, and the answer model all stay fixed, any observed difference is localized to the memory construction step. A matched four-condition intervention tests whether a record displaced by reordering actually carried task-relevant evidence: restoring that single record recovers over 60 percentage points of lost accuracy, while substituting a non-supporting record of equal length does not. We evaluate the protocol on PersonaMem-32K (63 primary queries, 29 users) and 470 LongMemEval-S questions with histories spanning 38 to 62 sessions, replicating the core intervention across five answer models. Survivor selection, defined as the choice of which record a cluster retains, drives most source-level changes, while different memory policies (compaction, bounded recency, MemoChat-style summarization, A-MEM) produce distinct failure signatures at the source, context, and metadata layers.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 30 of its 43 references that are in the map. First posted on arXiv 28 Sep 2026.

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30 of 43 references.

References · 30

  1. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,389
  2. 2025A-MEM: Agentic Memory for LLM Agentscited by 1,063
  3. 2023MemoryBank: Enhancing Large Language Models with Long-Term Memorycited by 556
  4. 2025Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactionscited by 254
  5. 2025Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scalecited by 178
  6. 2026MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agentscited by 142
  7. 2023MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversationcited by 97
  8. 2026MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Taskscited by 84
  9. 2024From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMscited by 79
  10. 2026AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applicationscited by 53
  11. 2026STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?cited by 50
  12. 2026From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agentscited by 37
18 more
  1. 2026Useful Memories Become Faulty When Continuously Updated by LLMscited by 20
  2. 2026Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agentscited by 20
  3. 2026Securing LLM-Agent Long-Term Memory Against Poisoning: Non-Malleable, Origin-Bound Authority with Machine-Checked Guaranteescited by 18
  4. 2026Reliable Post-Retrieval Assembly for Agent Memory: Separating Evidence Extraction from Policy Executioncited by 8
  5. 2026Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agentscited by 7
  6. 2026Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agentscited by 7
  7. 2026MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memorycited by 7
  8. 2026When Memory Updates but Behavior Does Not: Repairing Implicit Stale Dependencies in Personalized Agent Responsescited by 7
  9. 2026EMBER: Efficient Memory via Budgeted Evidence Retention for Long-Horizon Agentscited by 6
  10. 2026AttriMem: Attribution-Guided Process Feedback for Agent Memory Constructioncited by 5
  11. 2026Selection Integrity for LLM Graph Memory: An Accumulability Criterion for Information-Flow-Blind Retrievalcited by 4
  12. 2026When Stored Evidence Stops Being Usable: Scale-Conditioned Evaluation of Agent Memorycited by 3
  13. 2026Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agentscited by 3
  14. 2026When Not to Write Memory: Governing False Promotion from Correlated Agent Tracescited by 3
  15. 2026Ground Truth First: A Longitudinal Evaluation Instrument for Agent Memory, and the Tenure Crossover in Memory-Architecture Rankingscited by 3
  16. 2026Compiled Memory: Not More Information, but More Precise Instructions for Language Agentscited by 1
  17. 2026MemEvoBench: Benchmarking Safety Risks from Memory Misevolution in LLM Agentscited by 1
  18. 2026Success Is Not Self-Explanatory: Auditing Success Provenance in Agent Evaluationcited by 1

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