| Score-CAM: Score-weighted visual explanations for convolutional neural networks H Wang, Z Wang, M Du, F Yang, Z Zhang, S Ding, P Mardziel, X Hu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 1405* | 2020 |
| Explainability for large language models: A survey H Zhao, H Chen, F Yang, N Liu, H Deng, H Cai, S Wang, D Yin, M Du ACM Transactions on Intelligent Systems and Technology, 2024 | 332 | 2024 |
| Fairness in deep learning: A computational perspective M Du, F Yang, N Zou, X Hu IEEE Intelligent Systems 36 (4), 25-34, 2020 | 289 | 2020 |
| Data-centric artificial intelligence: A survey D Zha, ZP Bhat, KH Lai, F Yang, Z Jiang, S Zhong, X Hu arXiv preprint arXiv:2303.10158, 2023 | 223 | 2023 |
| An embarrassingly simple approach for trojan attack in deep neural networks R Tang, M Du, N Liu, F Yang, X Hu Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 197 | 2020 |
| XFake: Explainable fake news detector with visualizations F Yang, SK Pentyala, S Mohseni, M Du, H Yuan, R Linder, ED Ragan, S Ji, ... The World Wide Web Conference, 3600-3604, 2019 | 150 | 2019 |
| Evaluating explanation without ground truth in interpretable machine learning F Yang, M Du, X Hu arXiv preprint arXiv:1907.06831, 2019 | 108* | 2019 |
| Data-centric ai: Perspectives and challenges D Zha, ZP Bhat, KH Lai, F Yang, X Hu Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 100 | 2023 |
| Generalized demographic parity for group fairness Z Jiang, X Han, C Fan, F Yang, A Mostafavi, X Hu International Conference on Learning Representations, 2022 | 66 | 2022 |
| On attribution of recurrent neural network predictions via additive decomposition M Du, N Liu, F Yang, S Ji, X Hu The world wide web conference, 383-393, 2019 | 66 | 2019 |
| Machine learning explanations to prevent overtrust in fake news detection S Mohseni, F Yang, S Pentyala, M Du, Y Liu, N Lupfer, X Hu, S Ji, ... Proceedings of the international AAAI conference on web and social media 15 …, 2021 | 60 | 2021 |
| EXACT: Scalable graph neural networks training via extreme activation compression Z Liu, K Zhou, F Yang, L Li, R Chen, X Hu International Conference on Learning Representations, 2021 | 60 | 2021 |
| Learning credible deep neural networks with rationale regularization M Du, N Liu, F Yang, X Hu 2019 IEEE International Conference on Data Mining (ICDM), 150-159, 2019 | 57 | 2019 |
| Towards interpretation of recommender systems with sorted explanation paths F Yang, N Liu, S Wang, X Hu 2018 IEEE International Conference on Data Mining (ICDM), 667-676, 2018 | 38 | 2018 |
| Efficient xai techniques: A taxonomic survey YN Chuang, G Wang, F Yang, Z Liu, X Cai, M Du, X Hu arXiv preprint arXiv:2302.03225, 2023 | 37* | 2023 |
| Model-based counterfactual synthesizer for interpretation F Yang, SS Alva, J Chen, X Hu Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 37 | 2021 |
| Trust evolution over time in explainable AI for fake news detection S Mohseni, F Yang, S Pentyala, M Du, Y Liu, N Lupfer, X Hu, S Ji, ... Fair & Responsible AI Workshop at CHI 2020, 2020 | 34* | 2020 |
| Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Insertion R Tang, Q Feng, N Liu, F Yang, X Hu ACM SIGKDD Explorations, 2023 | 32* | 2023 |
| Large-scale heterogeneous feature embedding X Huang, Q Song, F Yang, X Hu Proceedings of the AAAI conference on artificial intelligence 33 (01), 3878-3885, 2019 | 32 | 2019 |
| Degree: Decomposition based explanation for graph neural networks Q Feng, N Liu, F Yang, R Tang, M Du, X Hu International Conference on Learning Representations, 2023 | 30 | 2023 |
Xia "Ben" HuAssociate Professor of Computer Science, Rice UniversityVerified email at rice.edu
