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ORCIDJesse Hoogland
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2020 – today
- 2025
[j2]Jesse Hoogland, George Wang, Matthew Farrugia-Roberts, Liam Carroll, Susan Wei, Daniel Murfet:
Loss Landscape Degeneracy and Stagewise Development in Transformers. Trans. Mach. Learn. Res. 2025 (2025)- [j1]Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeffrey Wu, Lucius Bushnaq, Nicholas Goldowsky-Dill, Stefan Heimersheim, Alejandro Ortega, Joseph Isaac Bloom, Stella Biderman, Adrià Garriga-Alonso, Arthur Conmy, Neel Nanda, Jessica Rumbelow, Martin Wattenberg, Nandi Schoots, Joseph Miller, William Saunders, Eric J. Michaud, Stephen Casper, Max Tegmark, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, Tom McGrath:
Open Problems in Mechanistic Interpretability. Trans. Mach. Learn. Res. 2025 (2025) - [c1]George Wang, Jesse Hoogland, Stan van Wingerden, Zach Furman, Daniel Murfet:
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient. ICLR 2025 - [i11]Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeff Wu, Lucius Bushnaq, Nicholas Goldowsky-Dill, Stefan Heimersheim, Alejandro Ortega, Joseph Isaac Bloom, Stella Biderman, Adrià Garriga-Alonso, Arthur Conmy, Neel Nanda, Jessica Rumbelow
, Martin Wattenberg, Nandi Schoots, Joseph Miller, Eric J. Michaud, Stephen Casper, Max Tegmark, William Saunders, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, Tom McGrath:
Open Problems in Mechanistic Interpretability. CoRR abs/2501.16496 (2025) - [i10]Liam Carroll, Jesse Hoogland, Matthew Farrugia-Roberts, Daniel Murfet:
Dynamics of Transient Structure in In-Context Linear Regression Transformers. CoRR abs/2501.17745 (2025) - [i9]Simon Pepin Lehalleur, Jesse Hoogland, Matthew Farrugia-Roberts, Susan Wei, Alexander Gietelink Oldenziel, George Wang, Liam Carroll, Daniel Murfet:
You Are What You Eat - AI Alignment Requires Understanding How Data Shapes Structure and Generalisation. CoRR abs/2502.05475 (2025) - [i8]Garrett Baker, George Wang, Jesse Hoogland, Daniel Murfet:
Studying Small Language Models with Susceptibilities. CoRR abs/2504.18274 (2025) - [i7]Rohan Hitchcock, Jesse Hoogland:
From Global to Local: A Scalable Benchmark for Local Posterior Sampling. CoRR abs/2507.21449 (2025) - [i6]Adam Maxwell, Zach Furman, Jesse Hoogland:
The Loss Kernel: A Geometric Probe for Deep Learning Interpretability. CoRR abs/2509.26537 (2025) - [i5]Philipp Alexander Kreer, Wilson Wu, Maxwell Adam, Zach Furman, Jesse Hoogland:
Bayesian Influence Functions for Hessian-Free Data Attribution. CoRR abs/2509.26544 (2025) - [i4]Jin Hwa Lee, Matthew Smith, Maxwell Adam, Jesse Hoogland:
Influence Dynamics and Stagewise Data Attribution. CoRR abs/2510.12071 (2025) - [i3]Einar Urdshals, Edmund Lau, Jesse Hoogland, Stan van Wingerden, Daniel Murfet:
Compressibility Measures Complexity: Minimum Description Length Meets Singular Learning Theory. CoRR abs/2510.12077 (2025) - 2024
- [i2]Jesse Hoogland, George Wang, Matthew Farrugia-Roberts, Liam Carroll, Susan Wei, Daniel Murfet:
The Developmental Landscape of In-Context Learning. CoRR abs/2402.02364 (2024) - [i1]George Wang, Jesse Hoogland, Stan van Wingerden, Zach Furman, Daniel Murfet:
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient. CoRR abs/2410.02984 (2024)
Coauthor Index
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