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Quantization-Robust Unlearning through the Lens of Retain-Forget Loss Landscapes Interaction
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Research finds post-training model quantization weakens LLM machine unlearning, potentially exposing previously removed private data.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 24 September 2026
- Collected by OneBench
- 25 Sept 2026, 03:01 UK
Stored source excerpt
arXiv:2609.27355v1 Announce Type: new Abstract: Unlearning ensures LLM compliance by removing the influence of private or copyrighted training data. However, since LLM models typically undergo…
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