| Lstm-based deep learning models for non-factoid answer selection M Tan, C Santos, B Xiang, B Zhou arXiv preprint arXiv:1511.04108, 2015 | 557 | 2015 |
| Attentive pooling networks C Santos, M Tan, B Xiang, B Zhou arXiv preprint arXiv:1602.03609, 2016 | 419 | 2016 |
| Improved representation learning for question answer matching M Tan, C Dos Santos, B Xiang, B Zhou Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 315 | 2016 |
| Large Scale Distributed Syntactic, Semantic and Lexical Language Models S Wang, M Tan US Patent App. 13/482,529, 2013 | 225 | 2013 |
| Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers H Wang, M Tan, M Yu, S Chang, D Wang, K Xu, X Guo, S Potdar ACL 2019, 2019 | 121 | 2019 |
| Multi-lingual evaluation of code generation models B Athiwaratkun, SK Gouda, Z Wang, X Li, Y Tian, M Tan, WU Ahmad, ... arXiv preprint arXiv:2210.14868, 2022 | 58 | 2022 |
| Out-of-Domain Detection for Low-Resource Text Classification Tasks M Tan, Y Yu, H Wang, D Wang, S Potdar, S Chang, M Yu Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 51 | 2019 |
| Discovering fine-grained sentiment in suicide notes W Wang, L Chen, M Tan, S Wang, AP Sheth Biomedical informatics insights 5, BII. S8963, 2012 | 46 | 2012 |
| DQ-BART: Efficient sequence-to-sequence model via joint distillation and quantization Z Li, Z Wang, M Tan, R Nallapati, P Bhatia, A Arnold, B Xiang, D Roth arXiv preprint arXiv:2203.11239, 2022 | 36 | 2022 |
| Direct optimization of ranking measures for learning to rank models M Tan, T Xia, L Guo, S Wang Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013 | 31 | 2013 |
| A scalable distributed syntactic, semantic, and lexical language model M Tan, W Zhou, L Zheng, S Wang Computational Linguistics 38 (3), 631-671, 2012 | 28 | 2012 |
| Context-aware conversation thread detection in multi-party chat M Tan, D Wang, Y Gao, H Wang, S Potdar, X Guo, S Chang, M Yu Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 25 | 2019 |
| Direct 0-1 loss minimization and margin maximization with boosting S Zhai, T Xia, M Tan, S Wang Advances in Neural Information Processing Systems 26, 2013 | 22 | 2013 |
| Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, and Bing Xiang B Athiwaratkun, SK Gouda, Z Wang, X Li, Y Tian, M Tan, WU Ahmad, ... Multi-lingual evaluation of code generation models, 2022 | 18 | 2022 |
| Crosscodeeval: A diverse and multilingual benchmark for cross-file code completion Y Ding, Z Wang, W Ahmad, H Ding, M Tan, N Jain, MK Ramanathan, ... Advances in Neural Information Processing Systems 36, 2024 | 17 | 2024 |
| Adversarial training data augmentation data for text classifiers M Tan, R Wang, I Padhi, S Potdar US Patent 11,093,707, 2021 | 14 | 2021 |
| Cross-domain multi-task learning for text classification M Tan, H Wang, L Kunc, Y Yu, S Potdar US Patent 10,937,416, 2021 | 14 | 2021 |
| A large scale distributed syntactic, semantic and lexical language model for machine translation M Tan, W Zhou, L Zheng, S Wang Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011 | 14 | 2011 |
| Group chat ecology in enterprise instant messaging: How employees collaborate through multi-user chat channels on slack D Wang, H Wang, M Yu, Z Ashktorab, M Tan Proceedings of the ACM on Human-Computer Interaction 6 (CSCW1), 1-14, 2022 | 13 | 2022 |
| Slack channels ecology in enterprises: How employees collaborate through group chat D Wang, H Wang, M Yu, Z Ashktorab, M Tan | 13 | 2021 |
Bing XiangHead of AI Research, Goldman SachsVerified email at gs.com
