| Effective approaches to attention-based neural machine translation MT Luong, H Pham, CD Manning arXiv preprint arXiv:1508.04025, 2015 | 10552 | 2015 |
| Electra: Pre-training text encoders as discriminators rather than generators K Clark, MT Luong, QV Le, CD Manning arXiv preprint arXiv:2003.10555, 2020 | 3914 | 2020 |
| Self-training with noisy student improves imagenet classification Q Xie, MT Luong, E Hovy, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 2637 | 2020 |
| Unsupervised data augmentation for consistency training Q Xie, Z Dai, E Hovy, MT Luong, QV Le arXiv preprint arXiv:1904.12848, 2019 | 2297 | 2019 |
| Qanet: Combining local convolution with global self-attention for reading comprehension AW Yu, D Dohan, MT Luong, R Zhao, K Chen, M Norouzi, QV Le arXiv preprint arXiv:1804.09541, 2018 | 1152 | 2018 |
| Towards a human-like open-domain chatbot D Adiwardana, MT Luong, DR So, J Hall, N Fiedel, R Thoppilan, Z Yang, ... arXiv preprint arXiv:2001.09977, 2020 | 1044 | 2020 |
| Addressing the rare word problem in neural machine translation MT Luong, I Sutskever, QV Le, O Vinyals, W Zaremba arXiv preprint arXiv:1410.8206, 2014 | 981 | 2014 |
| Multi-task sequence to sequence learning MT Luong, QV Le, I Sutskever, O Vinyals, L Kaiser arXiv preprint arXiv:1511.06114, 2015 | 941 | 2015 |
| 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 | 919 | 2023 |
| Scaling autoregressive models for content-rich text-to-image generation J Yu, Y Xu, JY Koh, T Luong, G Baid, Z Wang, V Vasudevan, A Ku, Y Yang, ... arXiv preprint arXiv:2206.10789 2 (3), 5, 2022 | 767 | 2022 |
| Meta pseudo labels H Pham, Z Dai, Q Xie, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 749 | 2021 |
| A hierarchical neural autoencoder for paragraphs and documents J Li, MT Luong, D Jurafsky arXiv preprint arXiv:1506.01057, 2015 | 739 | 2015 |
| Massive exploration of neural machine translation architectures D Britz, A Goldie, MT Luong, Q Le arXiv preprint arXiv:1703.03906, 2017 | 689 | 2017 |
| Stanford neural machine translation systems for spoken language domains MT Luong, CD Manning Proceedings of the 12th International Workshop on Spoken Language …, 2015 | 549 | 2015 |
| Achieving open vocabulary neural machine translation with hybrid word-character models MT Luong, CD Manning arXiv preprint arXiv:1604.00788, 2016 | 478 | 2016 |
| Semi-supervised sequence modeling with cross-view training K Clark, MT Luong, CD Manning, QV Le arXiv preprint arXiv:1809.08370, 2018 | 434 | 2018 |
| Bilingual word representations with monolingual quality in mind MT Luong, H Pham, CD Manning Proceedings of the 1st workshop on vector space modeling for natural …, 2015 | 417 | 2015 |
| Online and linear-time attention by enforcing monotonic alignments C Raffel, MT Luong, PJ Liu, RJ Weiss, D Eck International conference on machine learning, 2837-2846, 2017 | 308 | 2017 |
| When Are Tree Structures Necessary for Deep Learning of Representations? J Li, MT Luong, D Jurafsky, E Hovy arXiv preprint arXiv:1503.00185, 2015 | 269 | 2015 |
| Unsupervised data augmentation Q Xie, Z Dai, E Hovy, MT Luong, QV Le arXiv preprint arXiv:1904.12848 2 (6), 2019 | 262 | 2019 |
Quoc V. LeResearch Scientist, Google在 stanford.edu 的电子邮件经过验证
