| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1169 | 2022 |
| Brax--a differentiable physics engine for large scale rigid body simulation CD Freeman, E Frey, A Raichuk, S Girgin, I Mordatch, O Bachem arXiv preprint arXiv:2106.13281, 2021 | 322* | 2021 |
| Topology and geometry of half-rectified network optimization CD Freeman, J Bruna arXiv preprint arXiv:1611.01540, 2016 | 274 | 2016 |
| Multi-game decision transformers KH Lee, O Nachum, MS Yang, L Lee, D Freeman, S Guadarrama, ... Advances in Neural Information Processing Systems 35, 27921-27936, 2022 | 220 | 2022 |
| Modern approaches to exact diagonalization and selected configuration interaction with the adaptive sampling CI method NM Tubman, CD Freeman, DS Levine, D Hait, M Head-Gordon, ... Journal of chemical theory and computation 16 (4), 2139-2159, 2020 | 171 | 2020 |
| Understanding and correcting pathologies in the training of learned optimizers L Metz, N Maheswaranathan, J Nixon, D Freeman, J Sohl-Dickstein International Conference on Machine Learning, 4556-4565, 2019 | 168 | 2019 |
| Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet, 2024 A Templeton, T Conerly, J Marcus, J Lindsey, T Bricken, B Chen, ... URL https://transformer-circuits. pub/2024/scaling-monosemanticity 1, 2024 | 166* | 2024 |
| Gradients are not all you need L Metz, CD Freeman, SS Schoenholz, T Kachman arXiv preprint arXiv:2111.05803, 2021 | 85 | 2021 |
| Velo: Training versatile learned optimizers by scaling up L Metz, J Harrison, CD Freeman, A Merchant, L Beyer, J Bradbury, ... arXiv preprint arXiv:2211.09760, 2022 | 66 | 2022 |
| Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves L Metz, N Maheswaranathan, CD Freeman, B Poole, J Sohl-Dickstein arXiv preprint arXiv:2009.11243, 2020 | 58 | 2020 |
| Learning to predict without looking ahead: World models without forward prediction D Freeman, D Ha, L Metz Advances in Neural Information Processing Systems 32, 2019 | 46 | 2019 |
| Barkour: Benchmarking animal-level agility with quadruped robots K Caluwaerts, A Iscen, JC Kew, W Yu, T Zhang, D Freeman, KH Lee, ... arXiv preprint arXiv:2305.14654, 2023 | 41 | 2023 |
| Using a thousand optimization tasks to learn hyperparameter search strategies L Metz, N Maheswaranathan, R Sun, CD Freeman, B Poole, ... arXiv preprint arXiv:2002.11887, 2020 | 38 | 2020 |
| A method for the determination of speed-dependent semi-classical vector correlations from sliced image anisotropies MP Grubb, ML Warter, CD Freeman, NA West, KM Usakoski, KM Johnson, ... The Journal of chemical physics 135 (9), 2011 | 32* | 2011 |
| Practical tradeoffs between memory, compute, and performance in learned optimizers L Metz, CD Freeman, J Harrison, N Maheswaranathan, J Sohl-Dickstein Conference on Lifelong Learning Agents, 142-164, 2022 | 30 | 2022 |
| Improving large language model fine-tuning for solving math problems Y Liu, A Singh, CD Freeman, JD Co-Reyes, PJ Liu arXiv preprint arXiv:2310.10047, 2023 | 26 | 2023 |
| Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning S Kamyar Seyed Ghasemipour, D Freeman, B David, SS Gu, S Kataoka, ... arXiv e-prints, arXiv: 2203.13733, 2022 | 26* | 2022 |
| Relaxation dynamics of the toric code in contact with a thermal reservoir: Finite-size scaling in a low-temperature regime CD Freeman, CM Herdman, DJ Gorman, KB Whaley Physical Review B 90 (13), 134302, 2014 | 22 | 2014 |
| Transformer-based learned optimization E Gärtner, L Metz, M Andriluka, CD Freeman, C Sminchisescu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 19 | 2023 |
| Bi-manual manipulation and attachment via sim-to-real reinforcement learning S Kataoka, SKS Ghasemipour, D Freeman, I Mordatch arXiv preprint arXiv:2203.08277, 2022 | 15 | 2022 |
Luke MetzOpenAIVerified email at openai.com
