Rui Yan (严睿)
Rui Yan (严睿)
Renmin University of China. Previously with Peking U. and UPenn
Verified email at
Cited by
Cited by
Style transfer in text: Exploration and evaluation
Z Fu, X Tan, N Peng, D Zhao, R Yan
AAAI 2018, 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
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
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
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
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
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
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
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
Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems
C Tao, L Mou, D Zhao, R Yan
AAAI 2018, 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
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
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
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
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
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
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
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
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
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
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