Machine unlearning conflates reversing the influence of specific training examples (untraining) with removing the full underlying distribution or behavior (unlearning).
Feder Cooper, Christopher A
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Machine unlearning for online L-BFGS requires aligning the full optimizer state including memory to a counterfactual history without deleted samples rather than parameter correction alone.
Concept filtering of child images from training data offers only limited protection against CSAM generation in text-to-image models, as prompting strategies and fine-tuning can bypass filters even when most child images are removed.
A new extraction technique applied to 200 books and 14 LLMs finds that memorization of full books is rare except in specific high-capacity models where entire texts can be recovered verbatim.
citing papers explorer
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Is your algorithm unlearning or untraining?
Machine unlearning conflates reversing the influence of specific training examples (untraining) with removing the full underlying distribution or behavior (unlearning).
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Form and Function: Machine Unlearning as a Problem of Misaligned States
Machine unlearning for online L-BFGS requires aligning the full optimizer state including memory to a counterfactual history without deleted samples rather than parameter correction alone.
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Evaluating Concept Filtering Defenses against Child Sexual Abuse Material Generation by Text-to-Image Models
Concept filtering of child images from training data offers only limited protection against CSAM generation in text-to-image models, as prompting strategies and fine-tuning can bypass filters even when most child images are removed.
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Extracting memorized pieces of (copyrighted) books from open-weight language models
A new extraction technique applied to 200 books and 14 LLMs finds that memorization of full books is rare except in specific high-capacity models where entire texts can be recovered verbatim.
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