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Do LLMs Really Forget? Hidden-State Leakage in Model Unlearning and How to Fix it
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Research reveals LLM unlearning methods often leave sensitive data encoded in hidden representations despite output suppression.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 30 September 2026
- Collected by OneBench
- 1 Oct 2026, 03:02 UK
Stored source excerpt
arXiv:2609.36612v1 Announce Type: new Abstract: Unlearning in large language models (LLMs) is typically evaluated at the output level, where a model appears to suppress sensitive…
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