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Fan Yang
Fan Yang
Assistant Professor of Computer Science, Wake Forest University
Verified email at wfu.edu - Homepage
Title
Cited by
Cited by
Year
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
1067*2020
Fairness in deep learning: A computational perspective
M Du, F Yang, N Zou, X Hu
IEEE Intelligent Systems 36 (4), 25-34, 2020
2342020
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
1542020
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
1352019
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
1022023
Evaluating explanation without ground truth in interpretable machine learning
F Yang, M Du, X Hu
arXiv preprint arXiv:1907.06831, 2019
92*2019
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
712024
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
582019
Generalized demographic parity for group fairness
Z Jiang, X Han, C Fan, F Yang, A Mostafavi, X Hu
International Conference on Learning Representations, 2021
502021
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
492021
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
492019
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
422021
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
382023
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
342018
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
302019
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
25*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
252021
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
25*2020
How level of explanation detail affects human performance in interpretable intelligent systems: A study on explainable fact checking
R Linder, S Mohseni, F Yang, SK Pentyala, ED Ragan, XB Hu
Applied AI Letters 2 (4), e49, 2021
202021
Learning interpretable decision rule sets: a submodular optimization approach
F Yang, K He, L Yang, H Du, J Yang, B Yang, L Sun
Advances in Neural Information Processing Systems 34, 27890-27902, 2021
192021
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