One Thing to Fool them All: Generating Interpretable, Universal, and Physically-Realizable Adversarial Features. - Stephen Casper; Max Nadeau; Gabriel Kreiman (CoRR, 2021)

Robust Feature-Level Adversaries are Interpretability Tools. - Stephen Casper; Max Nadeau; Dylan Hadfield-Menell; Gabriel Kreiman (NeurIPS, 2022)

Discovering Variable Binding Circuitry with Desiderata. - Xander Davies; Max Nadeau; Nikhil Prakash; Tamar Rott Shaham; David Bau (CoRR, 2023)

Measurement Tampering Detection Benchmark. - Fabien Roger; Ryan Greenblatt; Max Nadeau; Buck Shlegeris; Nate Thomas (CoRR, 2023)

Circuit Breaking: Removing Model Behaviors with Targeted Ablation. - Maximilian Li; Xander Davies; Max Nadeau (CoRR, 2023)

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. - Stephen Casper; Xander Davies; Claudia Shi; Thomas Krendl Gilbert; Jérémy Scheurer; Javier Rando; Rachel Freedman; Tomasz Korbak; David Lindner; Pedro Freire; Tony Tong Wang; Samuel Marks; et al. (Trans. Mach. Learn. Res., 2023)