| Embedding entities and relations for learning and inference in knowledge bases B Yang, W Yih, X He, J Gao, L Deng arXiv preprint arXiv:1412.6575, 2014 | 3822 | 2014 |
| A diversity-promoting objective function for neural conversation models J Li, M Galley, C Brockett, J Gao, B Dolan arXiv preprint arXiv:1510.03055, 2015 | 2578 | 2015 |
| Deberta: Decoding-enhanced bert with disentangled attention P He, X Liu, J Gao, W Chen arXiv preprint arXiv:2006.03654, 2020 | 2471 | 2020 |
| Ms-celeb-1m: A dataset and benchmark for large-scale face recognition Y Guo, L Zhang, Y Hu, X He, J Gao Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 2418 | 2016 |
| Learning deep structured semantic models for web search using clickthrough data PS Huang, X He, J Gao, L Deng, A Acero, L Heck Proceedings of the 22nd ACM international conference on Information …, 2013 | 2356 | 2013 |
| MS MARCO: A human generated machine reading comprehension dataset T Nguyen arXiv preprint arXiv:1611.09268, 2016 | 2305 | 2016 |
| Stacked attention networks for image question answering Z Yang, X He, J Gao, L Deng, A Smola Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2286 | 2016 |
| On the variance of the adaptive learning rate and beyond L Liu, H Jiang, P He, W Chen, X Liu, J Gao, J Han arXiv preprint arXiv:1908.03265, 2019 | 2213 | 2019 |
| Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks X Li, X Yin, C Li, P Zhang, X Hu, L Zhang, L Wang, H Hu, L Dong, F Wei, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 2014 | 2020 |
| Domain-specific language model pretraining for biomedical natural language processing Y Gu, R Tinn, H Cheng, M Lucas, N Usuyama, X Liu, T Naumann, J Gao, ... ACM Transactions on Computing for Healthcare (HEALTH) 3 (1), 1-23, 2021 | 1816 | 2021 |
| Unified language model pre-training for natural language understanding and generation L Dong, N Yang, W Wang, F Wei, X Liu, Y Wang, J Gao, M Zhou, HW Hon Advances in neural information processing systems 32, 2019 | 1760 | 2019 |
| Deep learning--based text classification: a comprehensive review S Minaee, N Kalchbrenner, E Cambria, N Nikzad, M Chenaghlu, J Gao ACM computing surveys (CSUR) 54 (3), 1-40, 2021 | 1712 | 2021 |
| From captions to visual concepts and back H Fang, S Gupta, F Iandola, RK Srivastava, L Deng, P Dollár, J Gao, X He, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1662 | 2015 |
| Deep reinforcement learning for dialogue generation J Li, W Monroe, A Ritter, M Galley, J Gao, D Jurafsky arXiv preprint arXiv:1606.01541, 2016 | 1605 | 2016 |
| A latent semantic model with convolutional-pooling structure for information retrieval Y Shen, X He, J Gao, L Deng, G Mesnil Proceedings of the 23rd ACM international conference on conference on …, 2014 | 1602* | 2014 |
| 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 | 1518 | 2019 |
| Multi-task deep neural networks for natural language understanding X Liu, P He, W Chen, J Gao arXiv preprint arXiv:1901.11504, 2019 | 1424 | 2019 |
| A persona-based neural conversation model J Li, M Galley, C Brockett, GP Spithourakis, J Gao, B Dolan arXiv preprint arXiv:1603.06155, 2016 | 1297 | 2016 |
| Vinvl: Revisiting visual representations in vision-language models P Zhang, X Li, X Hu, J Yang, L Zhang, L Wang, Y Choi, J Gao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 1148* | 2021 |
| A neural network approach to context-sensitive generation of conversational responses A Sordoni, M Galley, M Auli, C Brockett, Y Ji, M Mitchell, JY Nie, J Gao, ... arXiv preprint arXiv:1506.06714, 2015 | 1142 | 2015 |
