| Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... Journal of Machine Learning Research 24 (240), 1-113, 2023 | 4609 | 2023 |
| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1548 | 2023 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1296 | 2023 |
| Program synthesis with large language models J Austin, A Odena, M Nye, M Bosma, H Michalewski, D Dohan, E Jiang, ... arXiv preprint arXiv:2108.07732, 2021 | 1041 | 2021 |
| Structured denoising diffusion models in discrete state-spaces J Austin, DD Johnson, J Ho, D Tarlow, R Van Den Berg Advances in Neural Information Processing Systems 34, 17981-17993, 2021 | 648 | 2021 |
| Show your work: Scratchpads for intermediate computation with language models M Nye, AJ Andreassen, G Gur-Ari, H Michalewski, J Austin, D Bieber, ... arXiv preprint arXiv:2112.00114, 2021 | 491 | 2021 |
| Gemma: Open models based on gemini research and technology G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ... arXiv preprint arXiv:2403.08295, 2024 | 440 | 2024 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 377 | 2024 |
| Scaling up models and data with t5x and seqio A Roberts, HW Chung, G Mishra, A Levskaya, J Bradbury, D Andor, ... Journal of Machine Learning Research 24 (377), 1-8, 2023 | 143 | 2023 |
| Language model cascades D Dohan, W Xu, A Lewkowycz, J Austin, D Bieber, RG Lopes, Y Wu, ... arXiv preprint arXiv:2207.10342, 2022 | 75 | 2022 |
| Program synthesis with large language models. CoRR abs/2108.07732 (2021) J Austin, A Odena, MI Nye, M Bosma, H Michalewski, D Dohan, E Jiang, ... arXiv preprint arXiv:2108.07732, 2021 | 50 | 2021 |
| Titan: A parallel asynchronous library for multi-agent and soft-body robotics using nvidia cuda J Austin, R Corrales-Fatou, S Wyetzner, H Lipson 2020 IEEE International Conference on Robotics and Automation (ICRA), 7754-7760, 2020 | 26 | 2020 |
| Beyond in-place corruption: Insertion and deletion in denoising probabilistic models DD Johnson, J Austin, R Berg, D Tarlow arXiv preprint arXiv:2107.07675, 2021 | 17 | 2021 |
| Measuring the impact of programming language distribution G Orlanski, K Xiao, X Garcia, J Hui, J Howland, J Malmaud, J Austin, ... International Conference on Machine Learning, 26619-26645, 2023 | 14 | 2023 |
| Resolving Code Review Comments with Machine Learning A Frömmgen, J Austin, P Choy, N Ghelani, L Kharatyan, G Surita, ... Proceedings of the 46th International Conference on Software Engineering …, 2024 | 4 | 2024 |
| Large vacuum flux surfaces generated by tilted planar coils JL Li, J Austin, KC Hammond, BY Israeli, FA Volpe Plasma physics and controlled fusion 61 (7), 075005, 2019 | 2 | 2019 |
| Machine-learned models for generating code snippets with predicted placeholders for optimizing software development DDW Johnson, DS Tarlow, M Tabachnyk, MH Rasi, J Austin, ... US Patent App. 18/618,371, 2024 | | 2024 |
| Machine-learned models for generating code snippets with predicted placeholders for optimizing software development DDW Johnson, DS Tarlow, M Tabachnyk, MH Rasi, J Austin, ... US Patent 11,972,234, 2024 | | 2024 |
| Prompting Machine-Learned Models Using Chains of Thought JW Wei, D Zhou, DE Schuurmans, QV Le, MP Bosma, EHH Chi, ... US Patent App. 17/881,746, 2023 | | 2023 |
| Using Chains of Thought to Prompt Machine-Learned Models Pre-Trained on Diversified Objectives JW Wei, D Zhou, X Wang, DE Schuurmans, QV Le, MP Bosma, EHH Chi, ... US Patent App. 18/160,776, 2023 | | 2023 |
Daniel TarlowResearch Scientist, Google DeepMind - MontrealVerified email at cs.toronto.edu
