| Language models represent space and time W Gurnee, M Tegmark ICLR 2024, 2023 | 186* | 2023 |
| Finding Neurons in a Haystack: Case Studies with Sparse Probing W Gurnee, N Nanda, M Pauly, K Harvey, D Troitskii, D Bertsimas Transactions of Machine Learning Research (TMLR), 2023 | 136* | 2023 |
| Refusal in language models is mediated by a single direction A Arditi, O Obeso, A Syed, D Paleka, N Panickssery, W Gurnee, N Nanda arXiv preprint arXiv:2406.11717, 2024 | 73* | 2024 |
| Learning sparse nonlinear dynamics via mixed-integer optimization D Bertsimas, W Gurnee Nonlinear Dynamics 111 (7), 6585-6604, 2023 | 45 | 2023 |
| Fairmandering: A column generation heuristic for fairness-optimized political districting W Gurnee, DB Shmoys SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21), 88-99, 2021 | 42 | 2021 |
| Not all language model features are linear J Engels, EJ Michaud, I Liao, W Gurnee, M Tegmark arXiv preprint arXiv:2405.14860, 2024 | 38* | 2024 |
| Universal neurons in GPT2 language models W Gurnee, T Horsley, ZC Guo, TR Kheirkhah, Q Sun, W Hathaway, ... Transactions of Machine Learning Research (TMLR), 2024 | 23* | 2024 |
| The Remarkable Robustness of LLMs: Stages of Inference? V Lad, W Gurnee, M Tegmark arXiv preprint arXiv:2406.19384, 2024 | 20* | 2024 |
| Combatting gerrymandering with social choice: The design of multi-member districts N Garg, W Gurnee, D Rothschild, D Shmoys Proceedings of the 23rd ACM Conference on Economics and Computation, 560-561, 2022 | 14 | 2022 |
| Sae reconstruction errors are (empirically) pathological W Gurnee AI Alignment Forum, 16, 2024 | 8* | 2024 |
| Confidence regulation neurons in language models A Stolfo, B Wu, W Gurnee, Y Belinkov, X Song, M Sachan, N Nanda arXiv preprint arXiv:2406.16254, 2024 | 6* | 2024 |
| Training Dynamics of Contextual N-Grams in Language Models L Quirke, L Heindrich, W Gurnee, N Nanda NeurIPS 2023 Workshop on Attributing Model Behavior at Scale, 2023 | 4 | 2023 |
| Multilevel interpretability of artificial neural networks: leveraging framework and methods from neuroscience Z He, J Achterberg, K Collins, K Nejad, D Akarca, Y Yang, W Gurnee, ... arXiv preprint arXiv:2408.12664, 2024 | 1 | 2024 |
| Scalable approximations of capacitated k-medians for political districting W Gurnee Technical report, Cornell University, Ithaca, United States, 2020 | 1 | 2020 |
Neel NandaMechanistic Interpretability Team Lead, Google DeepMinddeepmind.com의 이메일 확인됨