| Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension M Lewis, Y Liu, N Goyal, M Ghazvininejad, A Mohamed, O Levy, ... arXiv preprint arXiv:1910.13461, 2019 | 937 | 2019 |
| A knowledge-grounded neural conversation model M Ghazvininejad, C Brockett, MW Chang, B Dolan, J Gao, W Yih, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 330 | 2018 |
| Multilingual denoising pre-training for neural machine translation Y Liu, J Gu, N Goyal, X Li, S Edunov, M Ghazvininejad, M Lewis, ... Transactions of the Association for Computational Linguistics 8, 726-742, 2020 | 185 | 2020 |
| Mask-predict: Parallel decoding of conditional masked language models M Ghazvininejad, O Levy, Y Liu, L Zettlemoyer arXiv preprint arXiv:1904.09324, 2019 | 160* | 2019 |
| Generating Topical Poetry M Ghazvininejad, X Shi, Y Choi, K Knight Empirical Methods on Natural Language Processing, 2016 | 124 | 2016 |
| Hafez: an Interactive Poetry Generation System M Ghazvininejad, X Shi, J Priyadarshi, K Knight proceeding of ACL Demo Track, 2017 | 84 | 2017 |
| Towards controllable story generation N Peng, M Ghazvininejad, J May, K Knight Proceedings of the First Workshop on Storytelling, 43-49, 2018 | 77 | 2018 |
| Pre-training via paraphrasing M Lewis, M Ghazvininejad, G Ghosh, A Aghajanyan, S Wang, ... arXiv preprint arXiv:2006.15020, 2020 | 44 | 2020 |
| Training on synthetic noise improves robustness to natural noise in machine translation V Karpukhin, O Levy, J Eisenstein, M Ghazvininejad arXiv preprint arXiv:1902.01509, 2019 | 40 | 2019 |
| From local similarity to global coding: An application to image classification A Shaban, HR Rabiee, M Farajtabar, M Ghazvininejad Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 39 | 2013 |
| Non-autoregressive machine translation with disentangled context transformer J Kasai, J Cross, M Ghazvininejad, J Gu International Conference on Machine Learning, 5144-5155, 2020 | 25* | 2020 |
| Semi-autoregressive training improves mask-predict decoding M Ghazvininejad, O Levy, L Zettlemoyer arXiv preprint arXiv:2001.08785, 2020 | 20 | 2020 |
| Hierarchical active transfer learning D Kale, M Ghazvininejad, A Ramakrishna, J He, Y Liu Proceedings of the 2015 SIAM International Conference on Data Mining, 514-522, 2015 | 20 | 2015 |
| Aligned cross entropy for non-autoregressive machine translation M Ghazvininejad, V Karpukhin, L Zettlemoyer, O Levy International Conference on Machine Learning, 3515-3523, 2020 | 19 | 2020 |
| HMM based semi-supervised learning for activity recognition M Ghazvininejad, HR Rabiee, N Pourdamghani, P Khanipour Proceedings of the 2011 international workshop on Situation activity & goal …, 2011 | 16 | 2011 |
| Simple and effective retrieve-edit-rerank text generation N Hossain, M Ghazvininejad, L Zettlemoyer Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 13 | 2020 |
| Translating translationese: A two-step approach to unsupervised machine translation N Pourdamghani, N Aldarrab, M Ghazvininejad, K Knight, J May arXiv preprint arXiv:1906.05683, 2019 | 12 | 2019 |
| Neural poetry translation M Ghazvininejad, Y Choi, K Knight Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 11 | 2018 |
| Using word vectors to improve word alignments for low resource machine translation N Pourdamghani, M Ghazvininejad, K Knight Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 11 | 2018 |
| Isograph: Neighbourhood graph construction based on geodesic distance for semi-supervised learning M Ghazvininejad, M Mahdieh, HR Rabiee, PK Roshan, MH Rohban 2011 IEEE 11th International Conference on Data Mining, 191-200, 2011 | 9 | 2011 |
Luke ZettlemoyerUniversity of Washington; FacebookVerified email at cs.washington.edu
