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ETH Zurich

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TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering

QuestionHow robust are open-weight safeguards to modifications that preserve useful capability?

Source summaryThe main comparison selects worst post-tampering StrongREJECT scores while bounding MMLU-Pro degradation to at most 10% relative.

NUWA research note · independent review pending

Cross-cutting researchBehavior

Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples

QuestionDoes increasing clean-data scale dilute a fixed adversarial insertion enough to prevent a backdoor?

Source summaryComparable insertion counts can affect models trained on substantially different amounts of clean data.

NUWA research note · independent review pending