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.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.LG 2verdicts
UNVERDICTED 2representative citing papers
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
-
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.
-
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.