4 citations · 8 across the 9 of their papers we have counts for
5 papers · 1 filter
Obfuscated Activations Bypass LLM Latent-Space Defenses
Luke Bailey, Alex Serrano, Abhay Sheshadri +7
Recent latent-space monitoring techniques have shown promise as defenses against LLM attacks. These defenses act as scanners that seek to detect harmful activations before they lea…
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network
Erik Jenner, Shreyas Kapur, Vasil Georgiev +3
Do neural networks learn to implement algorithms such as look-ahead or search "in the wild"? Or do they rely purely on collections of simple heuristics? We present evidence of lear…
When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
Leon Lang, Davis Foote, Stuart Russell +3
Past analyses of reinforcement learning from human feedback (RLHF) assume that the human evaluators fully observe the environment. What happens when human feedback is based only on…
ALMANACS: A Simulatability Benchmark for Language Model Explainability
Edmund Mills, Shiye Su, Stuart Russell +1
How do we measure the efficacy of language model explainability methods? While many explainability methods have been developed, they are typically evaluated on bespoke tasks, preve…
Image Hijacks: Adversarial Images can Control Generative Models at Runtime
Luke Bailey, Euan Ong, Stuart Russell +1
Are foundation models secure against malicious actors? In this work, we focus on the image input to a vision-language model (VLM). We discover image hijacks, adversarial images tha…