The Goldilocks Zone: Towards Better Understanding of Neural Network Loss Landscapes. - Stanislav Fort; Adam Scherlis (AAAI, 2019)

Adversarial training for high-stakes reliability. - Daniel M. Ziegler; Seraphina Nix; Lawrence Chan; Tim Bauman; Peter Schmidt-Nielsen; Tao Lin; Adam Scherlis; Noa Nabeshima; Ben Weinstein-Raun; Daniel de Haas; Buck Shlegeris; Nate Thomas (NeurIPS, 2022)

Polysemanticity and Capacity in Neural Networks. - Adam Scherlis; Kshitij Sachan; Adam S. Jermyn; Joe Benton; Buck Shlegeris (CoRR, 2022)

Refusal in LLMs is an Affine Function. - Thomas Marshall; Adam Scherlis; Nora Belrose (CoRR, 2024)

Understanding Gradient Descent through the Training Jacobian. - Nora Belrose; Adam Scherlis (CoRR, 2024)

Estimating the Probability of Sampling a Trained Neural Network at Random. - Adam Scherlis; Nora Belrose (CoRR, 2025)