Zach Furman

According to our database, Zach Furman authored at least 5 papers between 2023 and 2025.

Collaborative distances:

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

2025

Bayesian Influence Functions for Hessian-Free Data Attribution.

Philipp Alexander Kreer, Wilson Wu, Maxwell Adam, Zach Furman, Jesse Hoogland

CoRR, September, 2025

The Loss Kernel: A Geometric Probe for Deep Learning Interpretability.

Adam Maxwell, Zach Furman, Jesse Hoogland

CoRR, September, 2025

Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient.

George Wang, Jesse Hoogland, Stan van Wingerden, Zach Furman, Daniel Murfet

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

The Local Learning Coefficient: A Singularity-Aware Complexity Measure.

Edmund Lau, Zach Furman, George Wang, Daniel Murfet, Susan Wei

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2023

Eliciting Latent Predictions from Transformers with the Tuned Lens.

Nora Belrose, Zach Furman, Logan Smith, Danny Halawi, Igor Ostrovsky, Lev McKinney, Stella Biderman, Jacob Steinhardt

CoRR, 2023