| Detecting rumors from microblogs with recurrent neural networks J Ma, W Gao, P Mitra, S Kwon, BJ Jansen, KF Wong, M Cha AAAI Press, 2016 | 1440 | 2016 |
| Detect rumors using time series of social context information on microblogging websites J Ma, W Gao, Z Wei, Y Lu, KF Wong Proceedings of the 24th ACM international on conference on information and …, 2015 | 767 | 2015 |
| Rumor detection on twitter with tree-structured recursive neural networks J Ma, W Gao, KF Wong Association for Computational Linguistics, 2018 | 700 | 2018 |
| Detect rumors in microblog posts using propagation structure via kernel learning J Ma, W Gao, KF Wong Association for Computational Linguistics, 2017 | 697 | 2017 |
| Wizardcoder: Empowering code large language models with evol-instruct Z Luo, C Xu, P Zhao, Q Sun, X Geng, W Hu, C Tao, J Ma, Q Lin, D Jiang ICLR 2024: The Twelfth International Conference on Learning Representations, 2023 | 457 | 2023 |
| Detect rumor and stance jointly by neural multi-task learning J Ma, W Gao, KF Wong Companion proceedings of the the web conference 2018, 585-593, 2018 | 270 | 2018 |
| Detect Rumors on Twitter by Promoting Information Campaigns with Generative Adversarial Learning J Ma, W Gao, KF Wong WWW2019, 2019 | 256 | 2019 |
| Sentence-level evidence embedding for claim verification with hierarchical attention networks J Ma, W Gao, S Joty, KF Wong Association for Computational Linguistics, 2019 | 109 | 2019 |
| From retweet to believability: Utilizing trust to identify rumor spreaders on twitter B Rath, W Gao, J Ma, J Srivastava Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017 | 87 | 2017 |
| Rumor detection on twitter with claim-guided hierarchical graph attention networks H Lin, J Ma, M Cheng, Z Yang, L Chen, G Chen EMNLP 2021: The 2021 Conference on Empirical Methods in Natural Language …, 2021 | 72 | 2021 |
| An attention-based rumor detection model with tree-structured recursive neural networks J Ma, W Gao, S Joty, KF Wong ACM Transactions on Intelligent Systems and Technology (TIST) 11 (4), 1-28, 2020 | 63 | 2020 |
| Debunking rumors on twitter with tree transformer J Ma, W Gao COLING 2020: Proceedings of the 28th International Conference on …, 2020 | 57 | 2020 |
| Detect rumors in microblog posts for low-resource domains via adversarial contrastive learning H Lin, J Ma, L Chen, Z Yang, M Cheng, G Chen Findings of the Association for Computational Linguistics: NAACL 2022, 2022 | 54 | 2022 |
| Zero-shot rumor detection with propagation structure via prompt learning H Lin, P Yi, J Ma, H Jiang, Z Luo, S Shi, R Liu Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 5213-5221, 2023 | 49 | 2023 |
| Cross-lingual covid-19 fake news detection J Du, Y Dou, C Xia, L Cui, J Ma, SY Philip 2021 International Conference on Data Mining Workshops (ICDMW), 859-862, 2021 | 47 | 2021 |
| Discovering attractive segments in the user-generated video streams Z Wang, J Zhou, J Ma, J Li, J Ai, Y Yang Information Processing & Management 57 (1), 102130, 2020 | 45 | 2020 |
| A weakly supervised propagation model for rumor verification and stance detection with multiple instance learning R Yang, J Ma, H Lin, W Gao Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 38 | 2022 |
| Augmented large language models with parametric knowledge guiding Z Luo, C Xu, P Zhao, X Geng, C Tao, J Ma, Q Lin, D Jiang arXiv preprint arXiv:2305.04757, 2023 | 37 | 2023 |
| Context-aware attentive multilevel feature fusion for named entity recognition Z Yang, J Ma, H Chen, J Zhang, Y Chang IEEE transactions on neural networks and learning systems 35 (1), 973-984, 2022 | 37 | 2022 |
| A coarse-to-fine cascaded evidence-distillation neural network for explainable fake news detection Z Yang, J Ma, H Chen, H Lin, Z Luo, Y Chang COLING 2022: The 29th International Conference on Computational Linguistics, 2022 | 35 | 2022 |
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