mlsanityData to 7 Oct 2026

Whose Memory Is It? Scope-Aware Commit Rules for Long-Term LLM Memory

arXiv 2610.09008 ↗First posted 6 Oct 2026cs.AIcited by 0

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

Abstract (arXiv)

Persistent memory allows an LLM agent to carry experience across conversations, but it also turns a local reasoning mistake into a durable one. During deliberation, an agent may consider a plan, simulate a tool result, report another speaker's belief, and then reject all of them. If memory retains only the resulting sentences, those once-useful possibilities can later return as facts. The record is neither fabricated nor irrelevant; it has simply been detached from the context in which it was valid. We identify this missing context as discourse ownership: the world, branch, or speaker that licenses a proposition. Our first finding is counterintuitive. Language models already carry a causally active signal for ownership, yet conventional memory interfaces discard it when they convert reasoning into records. We introduce CASK (Causally Anchored Scoping Keys), a commit rule that preserves this signal so that shared-world facts enter durable memory while provisional content remains available only within its original scope. Our second finding is that the most obvious way to preserve the signal---storing the discovered internal coordinates---is unreliable because equivalent representations need not keep the same coordinates. CASK instead preserves the stable relations that express ownership. Controlled long-conversation conflicts and tool-agent traces show that this design improves memory admission and prevents provisional content from contaminating later answers while complementing runtime provenance. The resulting commit boundary lets agents explore more possibilities without granting every intermediate sentence authority over future behavior.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. First posted on arXiv 6 Oct 2026.

Builds on

No reference list yet.

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Persistent Memory in Multi-Agent LLM Inference: What It Costs, What It Buys, and When You Can Tell
  2. 2026Remember, Verify, or Ask? Cross-Family Evaluation of Memory Commitment in LLM Agents
  3. 2026What Should an Agent Forget? Separating What Is Stored from What Is Used
  4. 2026STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?
  5. 2026Memory in the LLM Era: Modular Architectures and Strategies in a Unified Framework
  6. 2026ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control
  7. 2025Memory in Large Language Models: Mechanisms, Evaluation and Evolution
  8. 2026MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations