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Procedural Memory Under Change: Reuse and Interference in Controlled Web Tasks

arXiv 2609.09774 ↗First posted 9 Sep 2026cs.AIcited by 0

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Abstract (arXiv)

Procedural memory lets language agents reuse successful routines, but reuse presumes that a stored routine remains applicable. We study what happens when that presumption is deliberately violated. The study combines a retrospective, human-assisted interface-adaptation case from BrowserGym TimeWarp with controlled frozen-memory comparisons on synthetic shopping decisions. During the documented WebShop V1-V6 development path, interface-specific code was adapted while the separately stored high-level procedure was not reported to change; this phase does not constitute an autonomous memory-agent evaluation. In the controlled phase, an early pilot produced one task on which two memory conditions selected a more expensive item while the no-memory condition selected the reference minimum. Follow-up probes did not establish a recurring row-order or identity-binding pattern. We then tested four forms of mismatch: changed quantities, a different evidence representation, a conflict between local and global optimization, and distributed promotion evidence, across 32 formal cells. Each cell used one temperature-0 generation with the same local qwen3:8b configuration and no adaptive retry. Across these pairs, none of the predefined diagnostic interference signatures appeared on the tasks for which they were defined when current-task evidence was explicit and sufficient. The result identifies a tested region of non-interference: a procedural memory can be mismatched without becoming behaviorally disruptive. It does not establish general safety or a mechanism. The remaining question is which additional conditions turn applicability mismatch into observable, memory-caused error.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 12 references that are in the map. First posted on arXiv 9 Sep 2026.

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References · 10

  1. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  2. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  3. 2023ExpeL: LLM Agents Are Experiential Learnerscited by 814
  4. 2024Agent Workflow Memorycited by 342
  5. 2025ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memorycited by 253
  6. 2024The BrowserGym Ecosystem for Web Agent Researchcited by 152
  7. 2026Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluationcited by 8
  8. 2026TimeWarp: Evaluating Web Agents by Revisiting the Pastcited by 6
  9. 2026Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steeringcited by 2
  10. 2025WebArxiv: A Reproducible Benchmark for Evaluating Multimodal Web Agents on arXiv Taskscited by 1

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