| Newsqa: A machine comprehension dataset A Trischler, T Wang, X Yuan, J Harris, A Sordoni, P Bachman, K Suleman arXiv preprint arXiv:1611.09830, 2016 | 949 | 2016 |
| CAPTION-ing the situation: A lexically-derived taxonomy of psychological situation characteristics. S Parrigon, SE Woo, L Tay, T Wang Journal of personality and social psychology 112 (4), 642, 2017 | 262 | 2017 |
| Machine comprehension by text-to-text neural question generation X Yuan, T Wang, C Gulcehre, A Sordoni, P Bachman, S Subramanian, ... arXiv preprint arXiv:1705.02012, 2017 | 221 | 2017 |
| Exploring and predicting transferability across NLP tasks T Vu, T Wang, T Munkhdalai, A Sordoni, A Trischler, A Mattarella-Micke, ... arXiv preprint arXiv:2005.00770, 2020 | 160 | 2020 |
| One size does not fit all: Generating and evaluating variable number of keyphrases X Yuan, T Wang, R Meng, K Thaker, P Brusilovsky, D He, A Trischler arXiv preprint arXiv:1810.05241, 2018 | 141* | 2018 |
| Neural models for key phrase detection and question generation S Subramanian, T Wang, X Yuan, S Zhang, Y Bengio, A Trischler arXiv preprint arXiv:1706.04560, 2017 | 137 | 2017 |
| A joint model for question answering and question generation T Wang, X Yuan, A Trischler arXiv preprint arXiv:1706.01450, 2017 | 121 | 2017 |
| GPT-3-driven pedagogical agents to train children’s curious question-asking skills R Abdelghani, YH Wang, X Yuan, T Wang, P Lucas, H Sauzéon, ... International Journal of Artificial Intelligence in Education 34 (2), 483-518, 2024 | 106 | 2024 |
| Metalearned neural memory T Munkhdalai, A Sordoni, T Wang, A Trischler Advances in Neural Information Processing Systems 32, 2019 | 67 | 2019 |
| Automatic acquisition of lexical formality J Brooke, T Wang, G Hirst Coling 2010: Posters, 90-98, 2010 | 62 | 2010 |
| Diverse distributions of self-supervised tasks for meta-learning in NLP T Bansal, K Gunasekaran, T Wang, T Munkhdalai, A McCallum arXiv preprint arXiv:2111.01322, 2021 | 56 | 2021 |
| DSN-DDI: an accurate and generalized framework for drug–drug interaction prediction by dual-view representation learning Z Li, S Zhu, B Shao, X Zeng, T Wang, TY Liu Briefings in Bioinformatics 24 (1), bbac597, 2023 | 54 | 2023 |
| Structural insights into the SARS-CoV-2 Omicron RBD-ACE2 interaction J Lan, X He, Y Ren, Z Wang, H Zhou, S Fan, C Zhu, D Liu, B Shao, TY Liu, ... Cell research 32 (6), 593-595, 2022 | 54 | 2022 |
| Near-synonym lexical choice in latent semantic space T Wang, G Hirst Proceedings of the 23rd International Conference on Computational …, 2010 | 49 | 2010 |
| Exploring patterns in dictionary definitions for synonym extraction T Wang, G Hirst Natural Language Engineering 18 (3), 313-342, 2012 | 48 | 2012 |
| An empirical study on neural keyphrase generation R Meng, X Yuan, T Wang, S Zhao, A Trischler, D He arXiv preprint arXiv:2009.10229, 2020 | 47 | 2020 |
| Direct molecular conformation generation J Zhu, Y Xia, C Liu, L Wu, S Xie, Y Wang, T Wang, T Qin, W Zhou, H Li, ... arXiv preprint arXiv:2202.01356, 2022 | 44 | 2022 |
| Bringing structure into summaries: a faceted summarization dataset for long scientific documents R Meng, K Thaker, L Zhang, Y Dong, X Yuan, T Wang, D He arXiv preprint arXiv:2106.00130, 2021 | 44 | 2021 |
| Refining the notions of depth and density in wordnet-based semantic similarity measures T Wang, G Hirst Proceedings of the 2011 Conference on Empirical Methods in Natural Language …, 2011 | 39 | 2011 |
| Improved fragment sampling for ab initio protein structure prediction using deep neural networks T Wang, Y Qiao, W Ding, W Mao, Y Zhou, H Gong Nature Machine Intelligence 1 (8), 347-355, 2019 | 35 | 2019 |
Alessandro SordoniMicrosoft ResearchVerified email at microsoft.com
