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 | 684 | 2017 |
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 | 584 | 2022 |
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 | 475 | 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 | 235 | 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 | 224 | 2020 |
A hierarchical model for device placement A Mirhoseini*, A Goldie*, H Pham, B Steiner, QV Le, J Dean ICLR 2018, 2018 | 180 | 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 | 93 | 2023 |
Generating long and diverse responses with neural conversation models L Shao, S Gouws, D Britz, A Goldie, B Strope, R Kurzweil | 73 | 2016 |
Gap: Generalizable approximate graph partitioning framework A Nazi, W Hang, A Goldie, S Ravi, A Mirhoseini arXiv preprint arXiv:1903.00614, 2019 | 66 | 2019 |
Placement optimization with deep reinforcement learning A Goldie, A Mirhoseini Proceedings of the 2020 International Symposium on Physical Design, 3-7, 2020 | 52 | 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 | 51 | 2020 |
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 | 44 | 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 | 41 | 2022 |
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 | 40 | 2022 |
Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, and Jeff Dean. 2021. A graph placement … A Mirhoseini, A Goldie, M Yazgan, JW Jiang, E Songhori, S Wang, YJ Lee, ... Nature 594 (7862), 01, 2021 | 38 | 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 | 23* | 2020 |
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 |
Generating integrated circuit floorplans using neural networks CMR Ho, W Hang, MN Yazgan, AD Goldie, JA Dean, A Mirhoseini, ... US Patent 10,699,043, 2020 | 12 | 2020 |
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 | 10 | 2022 |
Delving into macro placement with reinforcement learning Z Jiang, E Songhori, S Wang, A Goldie, A Mirhoseini, J Jiang, YJ Lee, ... 2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD), 1-3, 2021 | 10 | 2021 |