mnadeau [at] college [dot] harvard [dot] edu
I'm Max Nadeau. I just graduated from Harvard College, where I studied computer science and did research on AI robustness and interpretability. Working with my collaborators, I developed techniques for altering (e.g. detoxifying) LLM behavior, localizing mechanisms for specific skills within models, and uncovering flaws in an image classifer that a human can put into words. These papers, respectively, are linked below.
I also enjoy mathematics, philosophy, and forecasting.
Send me an email and say hello, or connect on LinkedIn.
Li, M.*, Davies, X.*, & Nadeau, M.* (2023). Circuit Breaking: Removing Model Behaviors with Targeted Ablation. In 2023 ICML Workshop on Deployment Challenges for Generative AI.
Davies, X.*, Nadeau, M.*, Prakash, N.*, Shaham, T, & Bau, D. (2023). Discovering Variable Binding Circuitry with Desiderata. In 2023 ICML Workshop on Deployment Challenges for Generative AI.
Casper, S.*, Nadeau, M.*, Hadfield-Menell, D., & Kreiman, G. (2022). Robust Feature-Level Adversaries are Interpretability Tools. In NeurIPS 2022 (Advances in Neural Information Processing Systems 35).