WMDP is a public benchmark measuring hazardous LLM knowledge across biosecurity, cybersecurity, and chemical security, paired with RMU unlearning that reduces WMDP performance without degrading general capabilities.
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HarmBench is a new standardized benchmark for red teaming LLMs that supports large-scale comparisons of 18 attack methods and 33 models plus an efficient adversarial training defense.
Representation engineering uses population-level representations in deep neural networks to monitor and manipulate cognitive phenomena like honesty and harmlessness, providing simple effective baselines for LLM safety.
citing papers explorer
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The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning
WMDP is a public benchmark measuring hazardous LLM knowledge across biosecurity, cybersecurity, and chemical security, paired with RMU unlearning that reduces WMDP performance without degrading general capabilities.
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HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
HarmBench is a new standardized benchmark for red teaming LLMs that supports large-scale comparisons of 18 attack methods and 33 models plus an efficient adversarial training defense.
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Representation Engineering: A Top-Down Approach to AI Transparency
Representation engineering uses population-level representations in deep neural networks to monitor and manipulate cognitive phenomena like honesty and harmlessness, providing simple effective baselines for LLM safety.