| An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge Y Hao, Y Zhang, K Liu, S He, Z Liu, H Wu, J Zhao Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 428 | 2017 |
| A joint embedding method for entity alignment of knowledge bases Y Hao, Y Zhang, S He, K Liu, J Zhao Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big …, 2016 | 118 | 2016 |
| Question answering over knowledge base with neural attention combining global knowledge information Y Zhang, K Liu, S He, G Ji, Z Liu, H Wu, J Zhao arXiv preprint arXiv:1606.00979, 2016 | 82 | 2016 |
| Ontology matching with word embeddings Y Zhang, X Wang, S Lai, S He, K Liu, J Zhao, X Lv Chinese Computational Linguistics and Natural Language Processing Based on …, 2014 | 72 | 2014 |
| CASIA@ V2: A MLN-based Question Answering System over Linked Data. S He, Y Zhang, K Liu, J Zhao CLEF (Working Notes), 1249-1259, 2014 | 63 | 2014 |
| Machine reading comprehension using structural knowledge graph-aware network D Qiu, Y Zhang, X Feng, X Liao, W Jiang, Y Lyu, K Liu, J Zhao Proceedings of the 2019 conference on empirical methods in natural language …, 2019 | 51 | 2019 |
| MIE: A medical information extractor towards medical dialogues Y Zhang, Z Jiang, T Zhang, S Liu, J Cao, K Liu, S Liu, J Zhao Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 47 | 2020 |
| A joint model for question answering over multiple knowledge bases Y Zhang, S He, K Liu, J Zhao Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 47 | 2016 |
| Question answering over linked data using first-order logic S He, K Liu, Y Zhang, L Xu, J Zhao Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014 | 36 | 2014 |
| Alignment rationale for natural language inference Z Jiang, Y Zhang, Z Yang, J Zhao, K Liu Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 25 | 2021 |
| Question answering over knowledge bases K Liu, J Zhao, S He, Y Zhang IEEE Intelligent Systems 30 (5), 26-35, 2015 | 24 | 2015 |
| Scene restoring for narrative machine reading comprehension Z Tian, Y Zhang, K Liu, J Zhao, Y Jia, Z Sheng Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 16 | 2020 |
| Logic traps in evaluating attribution scores Y Ju, Y Zhang, Z Yang, Z Jiang, K Liu, J Zhao arXiv preprint arXiv:2109.05463, 2021 | 13 | 2021 |
| Menatqa: A new dataset for testing the temporal comprehension and reasoning abilities of large language models Y Wei, Y Su, H Ma, X Yu, F Lei, Y Zhang, J Zhao, K Liu arXiv preprint arXiv:2310.05157, 2023 | 11 | 2023 |
| Capturing sentence relations for answer sentence selection with multi-perspective graph encoding Z Tian, Y Zhang, X Feng, W Jiang, Y Lyu, K Liu, J Zhao Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 9032-9039, 2020 | 11 | 2020 |
| IAMA results for OAEI 2013. Y Zhang, X Wang, S He, K Liu, J Zhao, X Lv OM, 123-130, 2013 | 11 | 2013 |
| Representative Demonstration Selection for In-Context Learning with Two-Stage Determinantal Point Process Z Yang, Y Zhang, D Sui, C Liu, J Zhao, K Liu Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 8 | 2023 |
| Generative calibration for in-context learning Z Jiang, Y Zhang, C Liu, J Zhao, K Liu arXiv preprint arXiv:2310.10266, 2023 | 8 | 2023 |
| Enhancing multiple-choice machine reading comprehension by punishing illogical interpretations Y Ju, Y Zhang, Z Tian, K Liu, X Cao, W Zhao, J Li, J Zhao Proceedings of the 2021 conference on empirical methods in natural language …, 2021 | 8 | 2021 |
| Biomedical concept normalization by leveraging hypernyms C Yan, Y Zhang, K Liu, J Zhao, Y Shi, S Liu Proceedings of the 2021 conference on empirical methods in natural language …, 2021 | 8 | 2021 |
Kang Liu (刘康)Institute of Automation, Chinese Academy of SciencesПодтвержден адрес электронной почты в домене nlpr.ia.ac.cn