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Evading Chain-of-Thought Monitoring Through Model Poisoning
Chain-of-thought (CoT) monitoring is an increasingly important component of AI safety stacks but relies on the assumption that a model's reasoning trace is informative about its actions. This work studies the limits of CoT monitoring through the lens of model poisoning. We demonstrate that backdoors can be implanted in...
Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs
This work shows that a weaker, unaligned model can split a harmful task into benign-looking subproblems, consult a stronger aligned model independently on each, and combine the answers locally to laundering attack capability laundering.