| Accurate de novo prediction of protein contact map by ultra-deep learning model S Wang, S Sun, Z Li, R Zhang, J Xu PLoS computational biology 13 (1), e1005324, 2017 | 463 | 2017 |
| Patient knowledge distillation for bert model compression S Sun, Y Cheng, Z Gan, J Liu Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019 | 144 | 2019 |
| Dialogpt: Large-scale generative pre-training for conversational response generation Y Zhang, S Sun, M Galley, YC Chen, C Brockett, X Gao, J Gao, J Liu, ... arXiv preprint arXiv:1911.00536, 2019 | 143 | 2019 |
| Freelb: Enhanced adversarial training for natural language understanding C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu arXiv preprint arXiv:1909.11764, 2019 | 70* | 2019 |
| Analysis of deep learning methods for blind protein contact prediction in CASP12 S Wang, S Sun, J Xu Proteins: Structure, Function, and Bioinformatics 86, 67-77, 2018 | 64 | 2018 |
| Hierarchical graph network for multi-hop question answering Y Fang, S Sun, Z Gan, R Pillai, S Wang, J Liu Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019 | 32 | 2019 |
| Microsoft dialogue challenge: Building end-to-end task-completion dialogue systems X Li, Y Wang, S Sun, S Panda, J Liu, J Gao arXiv preprint arXiv:1807.11125, 2018 | 27 | 2018 |
| AUC-maximized deep convolutional neural fields for protein sequence labeling S Wang, S Sun, J Xu Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 24* | 2016 |
| Learning structured densities via infinite dimensional exponential families S Sun, M Kolar, J Xu Proceedings of the 28th International Conference on Neural Information …, 2015 | 22 | 2015 |
| An iterative network partition algorithm for accurate identification of dense network modules S Sun, X Dong, Y Fu, W Tian Nucleic Acids Research 40 (3), e18-e18, 2012 | 16 | 2012 |
| Learning scale-free networks by dynamic node specific degree prior Q Tang, S Sun, J Xu International Conference on Machine Learning, 2247-2255, 2015 | 13 | 2015 |
| Inferring block structure of graphical models in exponential families S Sun, H Wang, J Xu Artificial Intelligence and Statistics, 939-947, 2015 | 12 | 2015 |
| Adaptive variable clustering in gaussian graphical models S Sun, Y Zhu, J Xu Artificial Intelligence and Statistics, 931-939, 2014 | 9 | 2014 |
| Graphical model sketch B Kveton, H Bui, M Ghavamzadeh, G Theocharous, S Muthukrishnan, ... Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 7 | 2016 |
| FILTER: An enhanced fusion method for cross-lingual language understanding Y Fang, S Wang, Z Gan, S Sun, J Liu arXiv preprint arXiv:2009.05166, 2020 | 5 | 2020 |
| Contrastive Distillation on Intermediate Representations for Language Model Compression S Sun, Z Gan, Y Cheng, Y Fang, S Wang, J Liu Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 1 | 2020 |
| Cluster-former: Clustering-based sparse transformer for long-range dependency encoding S Wang, L Zhou, Z Gan, YC Chen, Y Fang, S Sun, Y Cheng, J Liu arXiv preprint arXiv:2009.06097, 2020 | 1 | 2020 |
| Accelerating Real-Time Question Answering via Question Generation Y Fang, S Wang, Z Gan, S Sun, J Liu arXiv preprint arXiv:2009.05167, 2020 | 1 | 2020 |
| Learning nonparametric forest graphical models with prior information Y Zhu, Z Liu, S Sun Artificial Intelligence and Statistics, 672-680, 2017 | 1 | 2017 |
| Cross-Thought for Sentence Encoder Pre-training S Wang, Y Fang, S Sun, Z Gan, Y Cheng, J Jiang, J Liu Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | | 2020 |
Jinbo XuProfessor, Toyota Technological Institute at ChicagoAdresse e-mail validée de ttic.edu
