| Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ... arXiv preprint arXiv:2307.15217, 2023 | 150 | 2023 |
| Towards understanding grokking: An effective theory of representation learning Z Liu, O Kitouni, NS Nolte, E Michaud, M Tegmark, M Williams Advances in Neural Information Processing Systems 35, 34651-34663, 2022 | 65 | 2022 |
| Omnigrok: Grokking beyond algorithmic data Z Liu, EJ Michaud, M Tegmark The Eleventh International Conference on Learning Representations, 2022 | 46 | 2022 |
| The quantization model of neural scaling E Michaud, Z Liu, U Girit, M Tegmark Advances in Neural Information Processing Systems 36, 2024 | 27 | 2024 |
| Understanding Learned Reward Functions EJ Michaud, A Gleave, S Russell arXiv preprint arXiv:2012.05862, 2020 | 26 | 2020 |
| Precision Machine Learning EJ Michaud, Z Liu, M Tegmark Entropy 25 (1), 175, 2023 | 15 | 2023 |
| Examining the Causal Structures of Deep Neural Networks Using Information Theory S Marrow, EJ Michaud, E Hoel Entropy 22 (12), 1429, 2020 | 6* | 2020 |
| Opening the AI black box: program synthesis via mechanistic interpretability EJ Michaud, I Liao, V Lad, Z Liu, A Mudide, C Loughridge, ZC Guo, ... arXiv preprint arXiv:2402.05110, 2024 | 1 | 2024 |
| Lunar Opportunities for SETI EJ Michaud, APV Siemion, J Drew, SP Worden arXiv preprint arXiv:2009.12689, 2020 | 1 | 2020 |
| Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models S Marks, C Rager, EJ Michaud, Y Belinkov, D Bau, A Mueller arXiv preprint arXiv:2403.19647, 2024 | | 2024 |
| SETI from the Lunar South Pole EJ Michaud, APV Siemion, J Drew, SP Worden | | |
Max TegmarkProfessor of Physics, MITVerified email at mit.edu
