Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
The paper discusses the safety risks associated with memory-equipped LLM agents over time. It highlights the concept of temporal memory contamination, where accumulated memory from previous tasks can negatively impact the agent's performance in future tasks. The authors propose a new evaluation protocol to assess memory safety longitudinally rather than at a single point in time.
- ▪Safety evaluations of memory-equipped LLM agents often focus on within-task safety under adversarial conditions.
- ▪The study introduces a trigger-probe protocol to evaluate memory safety across multiple independent tasks over time.
- ▪Results indicate that memory-induced violation rates increase with exposure length, suggesting that memory safety should be treated as a longitudinal property.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.17830 |
| Publication time | Tue, 19 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-19T04:04:57.272Z |
| Last seen | 2026-05-19T04:04:57.272Z |
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| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.17830 (cs) [Submitted on 18 May 2026] Title:Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents Authors:Ahmad Al-Tawaha, Shangding Gu, Peizhi Niu, Ruoxi Jia, Ming Jin View a PDF of the paper titled Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents, by Ahmad Al-Tawaha and 4 other authors View PDF HTML (experimental) Abstract:Safety evaluations of memory-equipped LLM agents typically measure within-task safety: whether an agent completes a single scenario safely, often under adversarial conditions such as prompt injection or memory poisoning.
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