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TopicsLarge language models LLM Safety Training Adversarial robustness

Tampering attacks expose limited robustness in RepNoise defenses against harmful fine-tuning of LLMs.

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https://arxiv.org/pdf/2408.00761 Untraced · nothing upstream recorded

We corroborate this in our comparisons, finding that the approaches in the latter two works lack robustness to the tampering attacks in our evaluations.

https://arxiv.org/pdf/2408.00761extraction 0.70

Related work on Rosati et al. immunization and RepNoise defenses against harmful fine-tuning

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