mlsanityData to 14 Oct 2026

When Stale Constraints Go Unchecked: Budgeted Verification Failures in Inherited Agent Memory

arXiv 2608.25553 ↗First posted 26 Aug 2026cs.IR cs.AI cs.CLcited by 3

On the map: LLM agents and tool use → Agent memory systems

Abstract (arXiv)

Provenance links keep the evidence behind an inherited belief reachable; an agent with a verification budget must still choose which links to inspect. We study a consolidated memory that states a decision constraint and whose source record has since been superseded by a record that withdraws it: provenance is immutable, the current record has changed, and the memory is stale. In a controlled six-memory scenario with a budget of two records, sixteen language models rarely re-verified a constraint that read as settled: they inspected its provenance path in about one episode in five and, once the constraint had been superseded, produced stale-consistent decisions in 77.3%, 74.7% and 74.7% of episodes across a primary run, a replication and a held-out domain. Re-assigning one of the same two slots to the critical path removed most of them: +74.0, +72.7 and +61.3 points (positive in every model), +80.7 in a prospectively frozen interleaved replication with a repaired non-critical control, and +62.0 on a panel of 10 models from 9 organisations; a corrected re-run of the held-out scenario gave +73.3. The forced-critical policy uses experimenter knowledge of the critical path: it quantifies how much stale-decision risk the same budget can recover and is not a scheduler. Two further deposited experiments locate the failure and a remedy: in this store the constraint's path is selected in 17.0% of episodes at two slots and 88.7% at four of six (above uniform allocation), and at two slots a one-sentence, target-blind rule (prefer memories that state a limit on a candidate direction) moved the agent's own allocation onto the constraint's path and recovered the oracle contrast on decisions (+89.3 points) where that constraint limits the tempting action, while a content-free freshness cue did not materially redirect allocation and a content-matched control rule changed neither selection nor decisions.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. Builds on 28 of its 57 references that are in the map. First posted on arXiv 26 Aug 2026.

Builds on

28 of 57 references.

Closest ancestors · 9

Same direction, newest first

  1. 2026When Memory Becomes Authority: Benchmarking Authority Collapse at the Memory Consolidation Boundary3 Aug
  2. 2026Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents25 Jun
  3. 2026Temporal Validity in Retrieval Memory: Eliminating Stale-Fact Errors for AI Agents over Evolving Knowledge25 Jun
  4. 2026When Does Belief-Based Agent Memory Help? Reliability-Conditional Updating and Provenance-Capped Poisoning Defense20 Jun
  5. 2026Reliable Post-Retrieval Assembly for Agent Memory: Separating Evidence Extraction from Policy Execution31 May
  6. 2026STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?7 May
  7. 2026From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents21 Apr
  8. 2025Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions7 Jul
  9. 2025Zep: A Temporal Knowledge Graph Architecture for Agent Memory20 Jan

Other references · 19

  1. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  2. 2024LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memorycited by 707
  3. 2023Active Retrieval Augmented Generationcited by 516
  4. 2023Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflictscited by 341
  5. 2026From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agentscited by 37
  6. 2026From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agentscited by 33
  7. 2026Securing LLM-Agent Long-Term Memory Against Poisoning: Non-Malleable, Origin-Bound Authority with Machine-Checked Guaranteescited by 18
  8. 2026From Lossy to Verified: A Provenance-Aware Tiered Memory for Agentscited by 17
  9. 2026Inference-Time Budget Control for LLM Search Agentscited by 13
  10. 2026Auditing Provenance Sensitivity in LLM Agent Action Selectioncited by 12
  11. 2026Failing to Falsify: Evaluating and Mitigating Confirmation Bias in Language Modelscited by 9
  12. 2026Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agentscited by 8
7 more
  1. 2026Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditingcited by 7
  2. 2026Omission Constraints Decay While Commission Constraints Persist in Long-Context LLM Agentscited by 5
  3. 2026TEPA: Revoking Stale Memories for Conflict-Robust Language Agentscited by 5
  4. 2026Selection Integrity for LLM Graph Memory: An Accumulability Criterion for Information-Flow-Blind Retrievalcited by 4
  5. 2026AllocBench: Measuring Online Tool Allocation Capability in LLM Agentscited by 2
  6. 2026Belief-Guided Inference Control for Large Language Model Services via Verifiable Observationscited by 1
  7. 2026Heteroskedastic Signals in Budgeted LLM Verification: Structural Heterogeneity Limits Optimization Gainscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026When Memory Updates but Behavior Does Not: Repairing Implicit Stale Dependencies in Personalized Agent Responses
  2. 2026PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents
  3. 2026MEMOREPAIR: Barrier-First Cascade Repair in Agentic Memory
  4. 2026Change-Provenant Supervision: Governing Learned Artifacts Under Policy Change ↗
  5. 2026Memory Is a Derivation: The Distributed-Evidence Paradox in Long-Term Agents
  6. 2026When Evidence Changes: Evaluating Memory Repair and Re-reading in Language-Model Agents
  7. 2026Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents
  8. 2026Impact Is Not Invalidation: Ask About the Claim, Not the Diff