WMDP Benchmark
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About
The Weapons of Mass Destruction Proxy (WMDP) benchmark is a dataset of 3,668 multiple-choice questions surrounding hazardous knowledge in biosecurity, cybersecurity, and chemical security. WMDP serves as both a proxy evaluation for hazardous knowledge in large language models (LLMs) and a benchmark for unlearning methods to remove such knowledge. To guide progress on mitigating risk from LLMs, RMU, a state-of-the-art unlearning method which reduces model performance on WMDP while maintaining general language model capabilities. The goal is to measure risks of malicious use by evaluating hazardous capabilities in LLMs, and improving inherent safety through machine unlearning.
Platform
Task
Features
• improves unlearning precision
• measures how llms could aid malicious actors.
• state-of-the-art unlearning method (rmu) to reduce model performance on wmdp.
• benchmark for unlearning methods.
• dataset of 3,668 multiple-choice questions surrounding hazardous knowledge in biosecurity, cybersecurity, and chemical security.
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