| Question answering on freebase via relation extraction and textual evidence K Xu, S Reddy, Y Feng, S Huang, D Zhao arXiv preprint arXiv:1603.00957, 2016 | 326 | 2016 |
| Semantic relation classification via convolutional neural networks with simple negative sampling K Xu, Y Feng, S Huang, D Zhao arXiv preprint arXiv:1506.07650, 2015 | 320 | 2015 |
| Multi-grained attention network for aspect-level sentiment classification F Fan, Y Feng, D Zhao Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 303 | 2018 |
| 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 | 213 | 2019 |
| Learning to predict charges for criminal cases with legal basis B Luo, Y Feng, J Xu, X Zhang, D Zhao arXiv preprint arXiv:1707.09168, 2017 | 210 | 2017 |
| Cross-lingual knowledge graph alignment via graph matching neural network K Xu, L Wang, M Yu, Y Feng, Y Song, Z Wang, D Yu arXiv preprint arXiv:1905.11605, 2019 | 189 | 2019 |
| Topic models for image annotation and text illustration Y Feng, M Lapata Human Language Technologies: The 2010 Annual Conference of the North …, 2010 | 163 | 2010 |
| Graph2seq: Graph to sequence learning with attention-based neural networks K Xu, L Wu, Z Wang, Y Feng, M Witbrock, V Sheinin arXiv preprint arXiv:1804.00823, 2018 | 161 | 2018 |
| Cail2018: A large-scale legal dataset for judgment prediction C Xiao, H Zhong, Z Guo, C Tu, Z Liu, M Sun, Y Feng, X Han, Z Hu, ... arXiv preprint arXiv:1807.02478, 2018 | 155 | 2018 |
| Visual information in semantic representation Y Feng, M Lapata Human language technologies: the 2010 Annual Conference of the North …, 2010 | 151 | 2010 |
| Automatic caption generation for news images Y Feng, M Lapata IEEE transactions on pattern analysis and machine intelligence 35 (4), 797-812, 2012 | 143 | 2012 |
| Answering natural language questions via phrasal semantic parsing K Xu, S Zhang, Y Feng, D Zhao Natural Language Processing and Chinese Computing: Third CCF Conference …, 2014 | 134* | 2014 |
| 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 ACL (2), 231-236, 2017 | 127 | 2017 |
| Yet another text captcha solver: A generative adversarial network based approach G Ye, Z Tang, D Fang, Z Zhu, Y Feng, P Xu, X Chen, Z Wang Proceedings of the 2018 ACM SIGSAC conference on computer and communications …, 2018 | 122 | 2018 |
| Automatic image annotation using auxiliary text information Y Feng, M Lapata Proceedings of ACL-08: HLT, 272-280, 2008 | 103 | 2008 |
| A convolution BiLSTM neural network model for Chinese event extraction Y Zeng, H Yang, Y Feng, Z Wang, D Zhao Natural Language Understanding and Intelligent Applications: 5th CCF …, 2016 | 102 | 2016 |
| Jointly learning entity and relation representations for entity alignment Y Wu, X Liu, Y Feng, Z Wang, D Zhao arXiv preprint arXiv:1909.09317, 2019 | 101 | 2019 |
| How many words is a picture worth? automatic caption generation for news images Y Feng, M Lapata Proceedings of the 48th annual meeting of the Association for Computational …, 2010 | 99 | 2010 |
| Learning with noise: Enhance distantly supervised relation extraction with dynamic transition matrix B Luo, Y Feng, Z Wang, Z Zhu, S Huang, R Yan, D Zhao arXiv preprint arXiv:1705.03995, 2017 | 88 | 2017 |
| Towards implicit content-introducing for generative short-text conversation systems L Yao, Y Zhang, Y Feng, D Zhao, R Yan Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 87 | 2017 |
Zheng WangProfessor of Intelligent Software Technology, University of LeedsEmail verificata su leeds.ac.uk
