RESEARCHMonitorWATCHLIST
An Information Bottleneck for Post-hoc Memorization Mitigation in LLMs
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Researchers proposed a plug-and-play variational information bottleneck framework to mitigate LLM training data memorization without retraining.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 6 November 2026
- Collected by OneBench
- 7 Nov 2026, 02:02 UK
Stored source excerpt
arXiv:2611.07669v1 Announce Type: new Abstract: Recent studies have shown that large language models (LLMs) can memorize and reproduce copyrighted training data, raising serious privacy and…
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