| Style transfer in text: Exploration and evaluation Z Fu, X Tan, N Peng, D Zhao, R Yan AAAI 2018, 2017 | 553 | 2017 |
| Natural language inference by tree-based convolution and heuristic matching L Mou, R Men, G Li, Y Xu, L Zhang, R Yan, Z Jin ACL 2016, 2016 | 407 | 2016 |
| Plan-and-write: Towards better automatic storytelling L Yao, N Peng, R Weischedel, K Knight, D Zhao, R Yan Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7378-7385, 2019 | 399 | 2019 |
| Learning to respond with deep neural networks for retrieval-based human-computer conversation system R Yan, Y Song, H Wu Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 393 | 2016 |
| How transferable are neural networks in nlp applications? L Mou, Z Meng, R Yan, G Li, Y Xu, L Zhang, Z Jin EMNLP 2016, 2016 | 363 | 2016 |
| Relation-aware entity alignment for heterogeneous knowledge graphs Y Wu, X Liu, Y Feng, Z Wang, R Yan, D Zhao arXiv preprint arXiv:1908.08210, 2019 | 348 | 2019 |
| Sequence to backward and forward sequences: A content-introducing approach to generative short-text conversation L Mou, Y Song, R Yan, G Li, L Zhang, Z Jin COLING 2016, 2016 | 289 | 2016 |
| Multi-view response selection for human-computer conversation X Zhou, D Dong, H Wu, S Zhao, D Yu, H Tian, X Liu, R Yan Proceedings of the 2016 conference on empirical methods in natural language …, 2016 | 271 | 2016 |
| Evolutionary timeline summarization: a balanced optimization framework via iterative substitution R Yan, X Wan, J Otterbacher, L Kong, X Li, Y Zhang Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011 | 254 | 2011 |
| Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems C Tao, L Mou, D Zhao, R Yan AAAI 2018, 2017 | 248 | 2017 |
| An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems. Y Song, R Yan, CT Li, JY Nie, M Zhang, D Zhao | 244* | 2018 |
| Citation count prediction: learning to estimate future citations for literature R Yan, J Tang, X Liu, D Shan, X Li Proceedings of the 20th ACM international conference on Information and …, 2011 | 235 | 2011 |
| Knowledge-grounded dialogue generation with pre-trained language models X Zhao, W Wu, C Xu, C Tao, D Zhao, R Yan arXiv preprint arXiv:2010.08824, 2020 | 202 | 2020 |
| Coherence constrained graph LSTM for group activity recognition J Tang, X Shu, R Yan, L Zhang IEEE transactions on pattern analysis and machine intelligence 44 (2), 636-647, 2019 | 187 | 2019 |
| Cgmh: Constrained sentence generation by metropolis-hastings sampling N Miao, H Zhou, L Mou, R Yan, L Li Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6834-6842, 2019 | 186 | 2019 |
| All in one: Exploring unified video-language pre-training J Wang, Y Ge, R Yan, Y Ge, KQ Lin, S Tsutsui, X Lin, G Cai, J Wu, Y Shan, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 177 | 2023 |
| Overcoming catastrophic forgetting for continual learning via model adaptation W Hu, Z Lin, B Liu, C Tao, ZT Tao, D Zhao, J Ma, R Yan International conference on learning representations, 2019 | 166 | 2019 |
| Get The Point of My Utterance! Learning Towards Effective Responses with Multi-Head Attention Mechanism. C Tao, S Gao, M Shang, W Wu, D Zhao, R Yan IJCAI, 4418-4424, 2018 | 150 | 2018 |
| Multi-representation fusion network for multi-turn response selection in retrieval-based chatbots C Tao, W Wu, C Xu, W Hu, D Zhao, R Yan Proceedings of the twelfth ACM international conference on web search and …, 2019 | 149 | 2019 |
| How to make context more useful? an empirical study on context-aware neural conversational models Z Tian, R Yan, L Mou, Y Song, Y Feng, D Zhao Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 149 | 2017 |
