Papers with corpora risk memorizing sensitive

1 papers
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models (2025.emnlp-main)

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Challenge: Large language models (LLMs) trained over corpora risk memorizing sensitive, copyrighted, or toxic content.
Approach: They propose a framework that removes targeted data while preserving model utility.
Outcome: The proposed framework resists membership inference attacks, minimizes impact on retained data, and maintains robustness across diverse scenarios.

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