| Constitutional ai: Harmlessness from ai feedback Y Bai, S Kadavath, S Kundu, A Askell, J Kernion, A Jones, A Chen, ... arXiv preprint arXiv:2212.08073, 2022 | 778 | 2022 |
| Massive exploration of neural machine translation architectures D Britz*, A Goldie*, T Luong, Q Le Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 704 | 2017 |
| A graph placement methodology for fast chip design A Mirhoseini*, A Goldie*, M Yazgan, JW Jiang, E Songhori, S Wang, ... Nature 594 (7862), 207-212, 2021 | 538 | 2021 |
| Generating high-quality and informative conversation responses with sequence-to-sequence models Y Shao, S Gouws, D Britz, A Goldie, B Strope, R Kurzweil Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 242 | 2017 |
| Chip placement with deep reinforcement learning A Mirhoseini*, A Goldie*, M Yazgan, J Jiang, E Songhori, S Wang, YJ Lee, ... arXiv preprint arXiv:2004.10746, 2020 | 239 | 2020 |
| A hierarchical model for device placement A Mirhoseini*, A Goldie*, H Pham, B Steiner, QV Le, J Dean ICLR 2018, 2018 | 185 | 2018 |
| The capacity for moral self-correction in large language models D Ganguli, A Askell, N Schiefer, TI Liao, K Lukošiūtė, A Chen, A Goldie, ... arXiv preprint arXiv:2302.07459, 2023 | 114 | 2023 |
| Generating long and diverse responses with neural conversation models L Shao, S Gouws, D Britz, A Goldie, B Strope, R Kurzweil | 76 | 2016 |
| Gap: Generalizable approximate graph partitioning framework A Nazi, W Hang, A Goldie, S Ravi, A Mirhoseini arXiv preprint arXiv:1903.00614, 2019 | 69 | 2019 |
| Measuring progress on scalable oversight for large language models SR Bowman, J Hyun, E Perez, E Chen, C Pettit, S Heiner, K Lukošiūtė, ... arXiv preprint arXiv:2211.03540, 2022 | 58 | 2022 |
| Placement optimization with deep reinforcement learning A Goldie, A Mirhoseini Proceedings of the 2020 International Symposium on Physical Design, 3-7, 2020 | 53 | 2020 |
| Transferable graph optimizers for ml compilers Y Zhou, S Roy, A Abdolrashidi, D Wong, P Ma, Q Xu, H Liu, ... Advances in Neural Information Processing Systems 33, 13844-13855, 2020 | 53 | 2020 |
| A full-stack search technique for domain optimized deep learning accelerators D Zhang, S Huda, E Songhori, K Prabhu, Q Le, A Goldie, A Mirhoseini Proceedings of the 27th ACM International Conference on Architectural …, 2022 | 51 | 2022 |
| Gdp: Generalized device placement for dataflow graphs Y Zhou, S Roy, A Abdolrashidi, D Wong, PC Ma, Q Xu, M Zhong, H Liu, ... arXiv preprint arXiv:1910.01578, 2019 | 46 | 2019 |
| Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, and Jeff Dean. A graph placement … A Mirhoseini, A Goldie, M Yazgan, JW Jiang, E Songhori, S Wang, YJ Lee, ... Nature 594 (7862), 207-212, 2021 | 41 | 2021 |
| Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Anand Babu, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, and Jeff Dean A Mirhoseini*, A Goldie*, M Yazgan, J Jiang, E Songhori, S Wang, YJ Lee, ... Chip placement with deep reinforcement learning, 2020 | 25* | 2020 |
| Raptor: Recursive abstractive processing for tree-organized retrieval P Sarthi, S Abdullah, A Tuli, S Khanna, A Goldie, CD Manning arXiv preprint arXiv:2401.18059, 2024 | 19 | 2024 |
| Automatic question generation and answer judging: a q&a game for language learning. Y Xu, A Goldie, S Seneff SLaTE, 57-60, 2009 | 18 | 2009 |
| Specific versus general principles for constitutional ai S Kundu, Y Bai, S Kadavath, A Askell, A Callahan, A Chen, A Goldie, ... arXiv preprint arXiv:2310.13798, 2023 | 13 | 2023 |
| Reinforcement learning for electronic design automation: Case studies and perspectives AF Budak, Z Jiang, K Zhu, A Mirhoseini, A Goldie, DZ Pan 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC), 500-505, 2022 | 13 | 2022 |
Quoc V. LeResearch Scientist, GoogleBestätigte E-Mail-Adresse bei stanford.edu
