| 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 | 124 | 2019 |
| Knowledge-grounded dialogue generation with pre-trained language models X Zhao, W Wu, C Xu, C Tao, D Zhao, R Yan EMNLP 2020, 2020 | 110 | 2020 |
| One time of interaction may not be enough: Go deep with an interaction-over-interaction network for response selection in dialogues C Tao, W Wu, C Xu, W Hu, D Zhao, R Yan Proceedings of the 57th annual meeting of the association for computational …, 2019 | 105 | 2019 |
| Low-Resource Knowledge-Grounded Dialogue Generation X Zhao, W Wu, C Tao, C Xu, D Zhao, R Yan ICLR-2020, 2020 | 74 | 2020 |
| A sequential matching framework for multi-turn response selection in retrieval-based chatbots Y Wu, W Wu, C Xing, C Xu, Z Li, M Zhou Computational Linguistics 45 (1), 163-197, 2019 | 74 | 2019 |
| Neural response generation with dynamic vocabularies Y Wu, W Wu, D Yang, C Xu, Z Li, M Zhou AAAI-2018, 2017 | 74 | 2017 |
| Knowledge enhanced hybrid neural network for text matching Y Wu, W Wu, X Can, Z Li, M Zhou AAAI-2018, 2016 | 42 | 2016 |
| Neural Response Generation with Meta-Words C Xu, W Wu, C Tao, H Hu, M Schuerman, Y Wang Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 36 | 2019 |
| Zero-Resource Knowledge-Grounded Dialogue Generation L Li, C Xu, W Wu, Y Zhao, X Zhao, C Tao NeurIPS 2020, 2020 | 35 | 2020 |
| ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation W Qi, Y Gong, Y Yan, C Xu, B Yao, B Zhou, B Cheng, D Jiang, J Chen, ... Demo of ACL 2021, 2021 | 31 | 2021 |
| A document-grounded matching network for response selection in retrieval-based chatbots X Zhao, C Tao, W Wu, C Xu, D Zhao, R Yan IJCAI-2019, 2019 | 30 | 2019 |
| Playing 20 question game with policy-based reinforcement learning H Hu, X Wu, B Luo, C Tao, C Xu, W Wu, Z Chen EMNLP 2018, 3233–3242, 2018 | 24 | 2018 |
| Towards explainable and controllable open domain dialogue generation with dialogue acts C Xu, W Wu, Y Wu arXiv preprint arXiv:1807.07255, 2018 | 24 | 2018 |
| Learning a Simple and Effective Model for Multi-turn Response Generation with Auxiliary Tasks Y Zhao, C Xu, W Wu EMNLP-2020, 2020 | 23 | 2020 |
| StyleDGPT: stylized response generation with pre-trained language models Z Yang, W Wu, C Xu, X Liang, J Bai, L Wang, W Wang, Z Li Findings of EMNLP 2020, 2020 | 18 | 2020 |
| Finetuning large-scale pre-trained language models for conversational recommendation with knowledge graph L Wang, H Hu, L Sha, C Xu, KF Wong, D Jiang arXiv preprint arXiv:2110.07477, 2021 | 17 | 2021 |
| Read, attend and comment: a deep architecture for automatic news comment generation Z Yang, C Xu, W Wu, Z Li EMNLP-2019, 2019 | 16 | 2019 |
| MPC-BERT: A Pre-Trained Language Model for Multi-Party Conversation Understanding JC Gu, C Tao, ZH Ling, C Xu, X Geng, D Jiang ACL 2021, 2021 | 15 | 2021 |
| Learning Neural Templates for Recommender Dialogue System Z Liang, H Hu, C Xu, J Miao, Y He, Y Chen, X Geng, F Liang, D Jiang EMNLP 2021, 2021 | 13 | 2021 |
| PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks Y Wang, C Xu, Q Sun, H Hu, C Tao, X Geng, D Jiang ACL 2022, 2022 | 10 | 2022 |
Chongyang TaoMicrosoftVerified email at microsoft.com
