| Advance and prospects of AdaBoost algorithm C Ying, M Qi-Guang, L Jia-Chen, G Lin Acta Automatica Sinica 39 (6), 745-758, 2013 | 464 | 2013 |
| Unimo: Towards unified-modal understanding and generation via cross-modal contrastive learning W Li, C Gao, G Niu, X Xiao, H Liu, J Liu, H Wu, H Wang arXiv preprint arXiv:2012.15409, 2020 | 341 | 2020 |
| Fedscale: Benchmarking model and system performance of federated learning at scale F Lai, Y Dai, S Singapuram, J Liu, X Zhu, H Madhyastha, M Chowdhury International conference on machine learning, 11814-11827, 2022 | 157 | 2022 |
| Leveraging graph to improve abstractive multi-document summarization W Li, X Xiao, J Liu, H Wu, H Wang, J Du arXiv preprint arXiv:2005.10043, 2020 | 139 | 2020 |
| RBoost: Label noise-robust boosting algorithm based on a nonconvex loss function and the numerically stable base learners Q Miao, Y Cao, G Xia, M Gong, J Liu, J Song IEEE transactions on neural networks and learning systems 27 (11), 2216-2228, 2015 | 84 | 2015 |
| Malware detection using bilayer behavior abstraction and improved one-class support vector machines Q Miao, J Liu, Y Cao, J Song International Journal of Information Security 15, 361-379, 2016 | 54 | 2016 |
| Faithfulness in natural language generation: A systematic survey of analysis, evaluation and optimization methods W Li, W Wu, M Chen, J Liu, X Xiao, H Wu arXiv preprint arXiv:2203.05227, 2022 | 44 | 2022 |
| Joint training of candidate extraction and answer selection for reading comprehension Z Wang, J Liu, X Xiao, Y Lyu, T Wu arXiv preprint arXiv:1805.06145, 2018 | 43 | 2018 |
| BASS: Boosting abstractive summarization with unified semantic graph W Wu, W Li, X Xiao, J Liu, Z Cao, S Li, H Wu, H Wang arXiv preprint arXiv:2105.12041, 2021 | 40 | 2021 |
| Exploring contextual word-level style relevance for unsupervised style transfer C Zhou, L Chen, J Liu, X Xiao, J Su, S Guo, H Wu arXiv preprint arXiv:2005.02049, 2020 | 36 | 2020 |
| PLANET: Dynamic content planning in autoregressive transformers for long-form text generation Z Hu, HP Chan, J Liu, X Xiao, H Wu, L Huang arXiv preprint arXiv:2203.09100, 2022 | 27 | 2022 |
| Modular ensembles for one-class classification based on density analysis J Liu, Q Miao, Y Sun, J Song, Y Quan Neurocomputing 171, 262-276, 2016 | 26 | 2016 |
| Research progress and prospect of Adaboost algorithm Y Cao, Q Miao, J Liu, L Gao J. Autom 17 (23), 342-351, 2013 | 25 | 2013 |
| Upainting: Unified text-to-image diffusion generation with cross-modal guidance W Li, X Xu, X Xiao, J Liu, H Yang, G Li, Z Wang, Z Feng, Q She, Y Lyu, ... arXiv preprint arXiv:2210.16031, 2022 | 23 | 2022 |
| SgSum: transforming multi-document summarization into sub-graph selection M Chen, W Li, J Liu, X Xiao, H Wu, H Wang arXiv preprint arXiv:2110.12645, 2021 | 20 | 2021 |
| Osiris: a malware behavior capturing system implemented at virtual machine monitor layer Y Cao, J Liu, Q Miao, W Li 2012 Eighth international conference on computational intelligence and …, 2012 | 20 | 2012 |
| Fast structural ensemble for one-class classification J Liu, Q Miao, Y Sun, J Song, Y Quan Pattern Recognition Letters 80, 179-187, 2016 | 19 | 2016 |
| Unimo-2: End-to-end unified vision-language grounded learning W Li, C Gao, G Niu, X Xiao, H Liu, J Liu, H Wu, H Wang arXiv preprint arXiv:2203.09067, 2022 | 18 | 2022 |
| Abstracting minimal security-relevant behaviors for malware analysis Y Cao, Q Miao, J Liu, L Gao Journal of Computer Virology and Hacking Techniques 9, 193-204, 2013 | 17 | 2013 |
| FENOC: an ensemble one-class learning framework for malware detection J Liu, J Song, Q Miao, Y Cao 2013 Ninth International Conference on Computational Intelligence and …, 2013 | 11 | 2013 |
