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ORCIDThomas McGrath 0001
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- affiliation: Goodfire Inc.
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2020 – today
- 2026
[i19]Raphaël Sarfati, Eric J. Bigelow, Daniel Wurgaft, Jack Merullo, Atticus Geiger, Owen Lewis, Tom McGrath, Ekdeep Singh Lubana:
The Shape of Beliefs: Geometry, Dynamics, and Interventions along Representation Manifolds of Language Models' Posteriors. CoRR abs/2602.02315 (2026)- [i18]Aaditya Vikram Prasad, Connor Watts, Jack Merullo, Dhruvil Gala, Owen Lewis, Thomas McGrath, Ekdeep Singh Lubana:
Features as Rewards: Scalable Supervision for Open-Ended Tasks via Interpretability. CoRR abs/2602.10067 (2026) - [i17]Satchel Grant, Victor Gillioz, Jake Ward, Thomas McGrath:
Shifting the Gradient: Understanding How Defensive Training Methods Protect Language Model Integrity. CoRR abs/2604.16423 (2026) - [i16]Sheridan Feucht, Tal Haklay, Usha Bhalla, Daniel Wurgaft, Can Rager, Raphaël Sarfati, Jack Merullo, Thomas McGrath, Owen Lewis, Ekdeep Singh Lubana, Thomas Fel, Atticus Geiger:
Arithmetic in the Wild: Llama uses Base-10 Addition to Reason About Cyclic Concepts. CoRR abs/2605.01148 (2026) - [i15]Daniel Wurgaft, Can Rager, Matthew Kowal, Vasudev Shyam, Sheridan Feucht, Usha Bhalla, Tal Haklay, Eric J. Bigelow, Raphaël Sarfati, Thomas McGrath, Owen Lewis, Jack Merullo, Noah D. Goodman, Thomas Fel, Atticus Geiger, Ekdeep Singh Lubana:
Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior. CoRR abs/2605.05115 (2026) - [i14]Eric J. Bigelow, Raphaël Sarfati, Daniel Wurgaft, Owen Lewis, Thomas McGrath, Jack Merullo, Atticus Geiger, Ekdeep Singh Lubana:
Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space. CoRR abs/2605.12412 (2026) - [i13]Leon Bergen, Usha Bhalla, Sidharth Baskaran, Max Loeffler, Raphaël Sarfati, Dhruvil Gala, Ryan Panwar, Santiago Aranguri, Thomas Fel, Atticus Geiger, Matthew Kowal, Siddharth Boppana, Daniel Balsam, Owen Lewis, Jack Merullo, Thomas McGrath, Ekdeep Singh Lubana:
Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal. CoRR abs/2606.12360 (2026) - [i12]Thomas Fel, Matthew Kowal, Mozes Jacobs, Dron Hazra, Usha Bhalla, Lee Sharkey, Lucius Bushnaq, Satchel Grant, Tal Haklay, Thomas Icard, Can Rager, Michael T. Pearce, Daniel Wurgaft, Aiden Swann, Fenil R. Doshi, Siddharth Boppana, Curt Tigges, Nick Cammarata, Thomas Serre, Vasudev Shyam, Owen Lewis, Thomas McGrath, Jack Merullo, Ekdeep Singh Lubana, Atticus Geiger:
Structuring Sparsity: Block-Sparse Featurizers Capture Visual Concept Manifolds. CoRR abs/2606.25234 (2026) - 2025
- [j3]Tom McGrath, Marc Schröder
:
Competitive secretary problem. Int. J. Game Theory 54(1): 1 (2025) - [j2]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) - [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]Eric J. Michaud, Liv Gorton, Tom McGrath:
Understanding sparse autoencoder scaling in the presence of feature manifolds. CoRR abs/2509.02565 (2025) - 2023
- [c2]David Lindner, János Kramár, Sebastian Farquhar, Matthew Rahtz, Tom McGrath, Vladimir Mikulik:
Tracr: Compiled Transformers as a Laboratory for Interpretability. NeurIPS 2023 - [i9]David Lindner, János Kramár, Matthew Rahtz, Thomas McGrath, Vladimir Mikulik:
Tracr: Compiled Transformers as a Laboratory for Interpretability. CoRR abs/2301.05062 (2023) - [i8]Thomas McGrath, Matthew Rahtz, János Kramár, Vladimir Mikulik, Shane Legg:
The Hydra Effect: Emergent Self-repair in Language Model Computations. CoRR abs/2307.15771 (2023) - [i7]Callum McDougall, Arthur Conmy, Cody Rushing, Thomas McGrath, Neel Nanda:
Copy Suppression: Comprehensively Understanding an Attention Head. CoRR abs/2310.04625 (2023) - [i6]Lisa Schut, Nenad Tomasev, Tom McGrath, Demis Hassabis, Ulrich Paquet, Been Kim:
Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero. CoRR abs/2310.16410 (2023) - 2021
- [j1]Ibrahim Ethem Bagci, Thomas McGrath, Christine Barthelmes, Scott Dean, RamÓn Bernardo Gavito, Robert J. Young, Utz Roedig:
Resonant-Tunnelling Diodes as PUF Building Blocks. IEEE Trans. Emerg. Top. Comput. 9(2): 878-885 (2021) - [i5]Grégoire Delétang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega:
Causal Analysis of Agent Behavior for AI Safety. CoRR abs/2103.03938 (2021) - [i4]Thomas McGrath, Andrei Kapishnikov, Nenad Tomasev, Adam Pearce, Demis Hassabis, Been Kim, Ulrich Paquet, Vladimir Kramnik:
Acquisition of Chess Knowledge in AlphaZero. CoRR abs/2111.09259 (2021) - 2020
- [c1]Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega:
Meta-trained agents implement Bayes-optimal agents. NeurIPS 2020 - [i3]Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega:
Meta-trained agents implement Bayes-optimal agents. CoRR abs/2010.11223 (2020) - [i2]Tim Genewein, Tom McGrath, Grégoire Delétang, Vladimir Mikulik, Miljan Martic, Shane Legg, Pedro A. Ortega:
Algorithms for Causal Reasoning in Probability Trees. CoRR abs/2010.12237 (2020)
2010 – 2019
- 2019
- [i1]Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew M. Botvinick, Shane Legg:
Meta-learning of Sequential Strategies. CoRR abs/1905.03030 (2019)
Coauthor Index
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