| Semantic relation classification via convolutional neural networks with simple negative sampling K Xu, Y Feng, S Huang, D Zhao EMNLP 2015, 2015 | 294 | 2015 |
| Question answering on freebase via relation extraction and textual evidence K Xu, S Reddy, Y Feng, S Huang, D Zhao ACL 2016, 2016 | 282 | 2016 |
| Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network K Xu, M Yu, Y Feng, Y Song, Z Wang, D Yu ACL 2019, 2019 | 141 | 2019 |
| Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks K Xu, L Wu, Z Wang, Y Feng, V Sheinin arXiv preprint arXiv:1804.00823, 2018 | 137 | 2018 |
| Durian: Duration informed attention network for multimodal synthesis C Yu, H Lu, N Hu, M Yu, C Weng, K Xu, P Liu, D Tuo, S Kang, G Lei, D Su, ... arXiv preprint arXiv:1909.01700, 2019 | 120 | 2019 |
| Answering natural language questions via phrasal semantic parsing K Xu, S Zhang, Y Feng, D Zhao Natural Language Processing and Chinese Computing, 333-344, 2014 | 110 | 2014 |
| Word Mover's Embedding: From Word2Vec to Document Embedding L Wu, IEH Yen, K Xu, F Xu, A Balakrishnan, PY Chen, P Ravikumar, ... EMNLP 2018, 2018 | 99 | 2018 |
| Extracting multiple-relations in one-pass with pre-trained transformers H Wang, M Tan, M Yu, S Chang, D Wang, K Xu, X Guo, S Potdar arXiv preprint arXiv:1902.01030, 2019 | 81 | 2019 |
| Exploiting rich syntactic information for semantic parsing with graph-to-sequence model K Xu, L Wu, Z Wang, M Yu, L Chen, V Sheinin EMNLP 2018, 2018 | 66 | 2018 |
| Enhancing key-value memory neural networks for knowledge based question answering K Xu, Y Lai, Y Feng, Z Wang Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 58 | 2019 |
| SQL-to-Text Generation with Graph-to-Sequence Model K Xu, L Wu, Z Wang, M Yu, L Chen, V Sheinin EMNLP 2018, 2018 | 51 | 2018 |
| Hybrid question answering over knowledge base and free text K Xu, Y Feng, S Huang, D Zhao Coling 2016, 2397-2407, 2016 | 46 | 2016 |
| Efficient processing of label-constraint reachability queries in large graphs L Zou, K Xu, JX Yu, L Chen, Y Xiao, D Zhao Information Systems 40, 47-66, 2014 | 35 | 2014 |
| Structural information preserving for graph-to-text generation L Song, A Wang, J Su, Y Zhang, K Xu, Y Ge, D Yu arXiv preprint arXiv:2102.06749, 2021 | 26 | 2021 |
| Improving weakly supervised visual grounding by contrastive knowledge distillation L Wang, J Huang, Y Li, K Xu, Z Yang, D Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 25 | 2021 |
| Lattice cnns for matching based chinese question answering Y Lai, Y Feng, X Yu, Z Wang, K Xu, D Zhao Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6634-6641, 2019 | 25 | 2019 |
| Answering label-constraint reachability in large graphs K Xu, L Zou, JX Yu, L Chen, Y Xiao, D Zhao Proceedings of the 20th ACM international conference on Information and …, 2011 | 24 | 2011 |
| Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment K Xu, L Song, Y Feng, Y Song, D Yu AAAI 2020, 2020 | 23 | 2020 |
| Scalable global alignment graph kernel using random features: From node embedding to graph embedding L Wu, IEH Yen, Z Zhang, K Xu, L Zhao, X Peng, Y Xia, C Aggarwal Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 21 | 2019 |
| Relation extraction exploiting full dependency forests L Jin, L Song, Y Zhang, K Xu, W Ma, D Yu Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8034-8041, 2020 | 19 | 2020 |
Yansong FengPeking UniversityПотвърден имейл адрес: pku.edu.cn
