Adam Scherlis

According to our database, Adam Scherlis authored at least 6 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Estimating the Probability of Sampling a Trained Neural Network at Random.

Adam Scherlis, Nora Belrose

CoRR, January, 2025

2024

Understanding Gradient Descent through the Training Jacobian.

Nora Belrose, Adam Scherlis

CoRR, 2024

Refusal in LLMs is an Affine Function.

Thomas Marshall, Adam Scherlis, Nora Belrose

CoRR, 2024

2022

Polysemanticity and Capacity in Neural Networks.

Adam Scherlis, Kshitij Sachan, Adam S. Jermyn, Joe Benton, Buck Shlegeris

CoRR, 2022

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2019

The Goldilocks Zone: Towards Better Understanding of Neural Network Loss Landscapes.

Stanislav Fort, Adam Scherlis

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019