AfterDeleteBench: Auditing Post-Deletion Information Persistence in LLM Agents
Factual evidence
What the source reports
Researchers introduced AfterDeleteBench to audit how LLM agents retain deleted memory data through derived states and summaries.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 23 October 2026
- Collected by OneBench
- 24 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2610.31366v1 Announce Type: cross Abstract: Many LLM agents maintain external persistent memory and derive additional state from past interactions, such as summaries. Deleting an original…
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The factual summary is a OneBench synthesis, not a quotation or independent verification. Collection time is not publication time. Open the source for its full context; related reporting can share the same underlying announcement.
OneBench interpretation
Institutional assessment
So what
Persistent memory deletion failures in LLM agents create data privacy and regulatory compliance vulnerabilities for financial institutions.
Do what
Review data deletion protocols with the team responsible for AI agent architecture before deploying persistent memory systems.