| Adversarial examples: Attacks and defenses for deep learning X Yuan, P He, Q Zhu, X Li IEEE transactions on neural networks and learning systems 30 (9), 2805-2824, 2019 | 1993 | 2019 |
| Single shot text detector with regional attention P He, W Huang, T He, Q Zhu, Y Qiao, X Li Proceedings of the IEEE international conference on computer vision, 3047-3055, 2017 | 376 | 2017 |
| GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text Q Zhu, X Li, A Conesa, C Pereira Bioinformatics 34 (9), 1547-1554, 2018 | 165 | 2018 |
| A batch normalized inference network keeps the KL vanishing away Q Zhu, J Su, W Bi, X Liu, X Ma, X Li, D Wu arXiv preprint arXiv:2004.12585, 2020 | 70 | 2020 |
| Improving question generation with sentence-level semantic matching and answer position inferring X Ma, Q Zhu, Y Zhou, X Li Proceedings of the AAAI conference on artificial intelligence 34 (05), 8464-8471, 2020 | 64 | 2020 |
| GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model Q Zhu, Z Feng, X Li Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 57 | 2018 |
| Don't Parse, Insert: Multilingual Semantic Parsing with Insertion Based Decoding Q Zhu, H Khan, S Soltan, S Rawls, W Hamza arXiv preprint arXiv:2010.03714, 2020 | 27 | 2020 |
| Learning fast and slow: Propedeutica for real-time malware detection R Sun, X Yuan, P He, Q Zhu, A Chen, A Gregio, D Oliveira, X Li IEEE Transactions on Neural Networks and Learning Systems 33 (6), 2518-2529, 2021 | 18 | 2021 |
| Local contextual attention with hierarchical structure for dialogue act recognition Z Dai, J Fu, Q Zhu, H Cui, Y Qi arXiv preprint arXiv:2003.06044, 2020 | 14 | 2020 |
| Statistical learning for semantic parsing: A survey Q Zhu, X Ma, X Li Big Data Mining and Analytics 2 (4), 217-239, 2019 | 14 | 2019 |
| Asking complex questions with multi-hop answer-focused reasoning X Ma, Q Zhu, Y Zhou, X Li, D Wu arXiv preprint arXiv:2009.07402, 2020 | 6 | 2020 |
| Character sequence-to-sequence model with global attention for universal morphological reinflection Q Zhu, Y Li, X Li Proceedings of the CoNLL SIGMORPHON 2017 Shared Task: Universal …, 2017 | 5 | 2017 |
Xiaolin (Andy) LiChief AI Scientist, Hangzhou Institute of Medicine, Chinese Academy of Sciences在 cognization.com 的电子邮件经过验证
