| Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... nature 575 (7782), 350-354, 2019 | 5199 | 2019 |
| Deep speech 2: End-to-end speech recognition in english and mandarin D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ... International conference on machine learning, 173-182, 2016 | 3965 | 2016 |
| Emergent abilities of large language models J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... arXiv preprint arXiv:2206.07682, 2022 | 3592* | 2022 |
| Part-of-speech tagging for twitter: Annotation, features, and experiments K Gimpel, N Schneider, B O’connor, D Das, DP Mills, J Eisenstein, ... Proceedings of the 49th annual meeting of the Association for Computational …, 2011 | 1349 | 2011 |
| On the cross-lingual transferability of monolingual representations M Artetxe, S Ruder, D Yogatama arXiv preprint arXiv:1910.11856, 2019 | 801 | 2019 |
| Program induction by rationale generation: Learning to solve and explain algebraic word problems W Ling, D Yogatama, C Dyer, P Blunsom arXiv preprint arXiv:1705.04146, 2017 | 678 | 2017 |
| AlphaStar: Mastering the Real-Time Strategy Game StarCraft II O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, W Czarnecki, ... | 583 | 2019 |
| Random feature attention H Peng, N Pappas, D Yogatama, R Schwartz, NA Smith, L Kong arXiv preprint arXiv:2103.02143, 2021 | 385 | 2021 |
| Generative and discriminative text classification with recurrent neural networks D Yogatama, C Dyer, W Ling, P Blunsom arXiv preprint arXiv:1703.01898, 2017 | 276 | 2017 |
| Efficient Transfer Learning Method for Automatic Hyperparameter Tuning D Yogatama, G Mann Proceedings of the 17th International Conference on Artificial Intelligence …, 2014 | 270 | 2014 |
| Episodic memory in lifelong language learning C de Masson D'Autume, S Ruder, L Kong, D Yogatama Advances in Neural Information Processing Systems 32, 2019 | 254 | 2019 |
| Sparse overcomplete word vector representations M Faruqui, Y Tsvetkov, D Yogatama, C Dyer, N Smith ACL 2015, 2015 | 253 | 2015 |
| A contrastive framework for neural text generation Y Su, T Lan, Y Wang, D Yogatama, L Kong, N Collier Advances in Neural Information Processing Systems 35, 21548-21561, 2022 | 223 | 2022 |
| Learning and evaluating general linguistic intelligence D Yogatama, CM d'Autume, J Connor, T Kocisky, M Chrzanowski, L Kong, ... arXiv preprint arXiv:1901.11373, 2019 | 223* | 2019 |
| Reducing sentiment bias in language models via counterfactual evaluation PS Huang, H Zhang, R Jiang, R Stanforth, J Welbl, J Rae, V Maini, ... arXiv preprint arXiv:1911.03064, 2019 | 217 | 2019 |
| Learning to compose words into sentences with reinforcement learning D Yogatama, P Blunsom, C Dyer, E Grefenstette, W Ling arXiv preprint arXiv:1611.09100, 2016 | 210 | 2016 |
| Mind the gap: Assessing temporal generalization in neural language models A Lazaridou, A Kuncoro, E Gribovskaya, D Agrawal, A Liska, T Terzi, ... Advances in Neural Information Processing Systems 34, 29348-29363, 2021 | 201* | 2021 |
| Achieving verified robustness to symbol substitutions via interval bound propagation PS Huang, R Stanforth, J Welbl, C Dyer, D Yogatama, S Gowal, ... arXiv preprint arXiv:1909.01492, 2019 | 188 | 2019 |
| Emergent abilities of large language models. arXiv J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... arXiv preprint arXiv:2206.07682 10, 2022 | 174 | 2022 |
| LSTMs can learn syntax-sensitive dependencies well, but modeling structure makes them better A Kuncoro, C Dyer, J Hale, D Yogatama, S Clark, P Blunsom Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 172 | 2018 |
Noah A. SmithUniversity of Washington; Allen Institute for Artificial Intelligence在 cs.washington.edu 的电子邮件经过验证
