Research
Graph Neural Networks, Graph Neural Network
Large Language Models, Large Language Model
Artificial Intelligence
Data Attribution
Explainable AI
Responsible AI
Trustworthy AI
Copyright
Generative AI
Deep Learning
Neural Network Models, Neural Network Modelling, Neural Network Model
List of Publications (38)
In 2024
38
Fair machine unlearning: Data removal while mitigating disparities. A Oesterling, J Ma, F Calmon, H Lakkaraju International Conference on Artificial Intelligence and Statistics, 3736-3744, 2024.
Found on Publication Page
37
Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications. Y Liu, S Gautam, J Ma, H Lakkaraju Proceedings of the 2024 Conference of the North American Chapter of the ..., 2024.
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36
OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning. J Ma, V Lai, Y Zhang, C Chen, P Hamilton, D Ljubenkov, H Lakkaraju, ... arXiv preprint arXiv:2403.05565, 2024.
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35
A metadata-driven approach to understand graph neural networks. TW Li, Q Mei, J Ma Advances in Neural Information Processing Systems 36, 2024.
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34
AI Risk Management Should Incorporate Both Safety and Security. X Qi, Y Huang, Y Zeng, E Debenedetti, J Geiping, L He, K Huang, ... arXiv preprint arXiv:2405.19524, 2024.
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33
Efficient Ensembles Improve Training Data Attribution. J Deng, TW Li, S Zhang, J Ma arXiv preprint arXiv:2405.17293, 2024.
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32
Towards Reliable Empirical Machine Unlearning Evaluation: A Game-Theoretic View. Y Tu, P Hu, J Ma arXiv preprint arXiv:2404.11577, 2024.
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31
PM2. 5 forecasting under distribution shift: A graph learning approach. Y Liu, J Ma, P Dhillon, Q Mei AI Open 5, 23-29, 2024.
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In 2023
30
Post Hoc Explanations of Language Models Can Improve Language Models. S Krishna, J Ma, D Slack, A Ghandeharioun, S Singh, H Lakkaraju arXiv preprint arXiv:2305.11426, 2023.
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29
Can llms effectively leverage graph structural information: when and why. J Huang, X Zhang, Q Mei, J Ma arXiv preprint arXiv:2309.16595, 2023.
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28
Analyzing chain-of-thought prompting in large language models via gradient-based feature attributions. S Wu, EM Shen, C Badrinath, J Ma, H Lakkaraju arXiv preprint arXiv:2307.13339, 2023.
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27
Towards bridging the gaps between the right to explanation and the right to be forgotten. S Krishna, J Ma, H Lakkaraju International Conference on Machine Learning, 17808-17826, 2023.
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26
Computational copyright: Towards a royalty model for ai music generation platforms. J Deng, J Ma arXiv preprint arXiv:2312.06646, 2023.
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25
Accurate, Explainable, and Private Models: Providing Recourse While Minimizing Training Data Leakage. C Huang, C Swoopes, C Xiao, J Ma, H Lakkaraju arXiv preprint arXiv:2308.04341, 2023.
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24
Copyright and Artificial Intelligence (AI). GS Balasubramaniam, SR Benson, AS Chan, K Jacobs, KV Jenkins, ... Federal Register, 2023.
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23
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). J Ma, J Zhu, Y Dong, D Koutra, J He, Q Mei, A Tsitsulin, X Zhang, M Zitnik Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and ..., 2023.
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In 2022
22
Adversarial attack on graph neural networks as an influence maximization problem. J Ma, J Deng, Q Mei Proceedings of the fifteenth ACM international conference on web search and ..., 2022.
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21
Soden: A scalable continuous-time survival model through ordinary differential equation networks. W Tang, J Ma, Q Mei, J Zhu Journal of Machine Learning Research 23 (34), 1-29, 2022.
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20
Partition-based active learning for graph neural networks. J Ma, Z Ma, J Chai, Q Mei arXiv preprint arXiv:2201.09391, 2022.
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19
Graph learning indexer: A contributor-friendly and metadata-rich platform for graph learning benchmarks. J Ma, X Zhang, H Fan, J Huang, T Li, TW Li, Y Tu, C Zhu, Q Mei Learning on Graphs Conference, 7: 1-7: 23, 2022.
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18
Fast learning of MNL model from general partial rankings with application to network formation modeling. J Ma, X Zhang, Q Mei Proceedings of the Fifteenth ACM International Conference on Web Search and ..., 2022.
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In 2021
16
Subgroup generalization and fairness of graph neural networks. J Ma, J Deng, Q Mei Advances in Neural Information Processing Systems 34, 1048-1061, 2021.
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15
How much space has been explored? measuring the chemical space covered by databases and machine-generated molecules. Y Xie, Z Xu, J Ma, Q Mei arXiv preprint arXiv:2112.12542, 2021.
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14
Learning-to-rank with partitioned preference: Fast estimation for the Plackett-Luce model. J Ma, X Yi, W Tang, Z Zhao, L Hong, E Chi, Q Mei International Conference on Artificial Intelligence and Statistics, 928-936, 2021.
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13
A Simple Yet Effective Method Improving Graph Fingerprints for Graph-Level Prediction. J Ying, J Ma, Q Mei Proceedings of the 2021 Workshop on Graph Learning Benchmarks (GLB'21), 1-9, 2021.
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12
GReS: Workshop on graph neural networks for recommendation and search. T Thonet, S Clinchant, C Lassance, E Isufi, J Ma, Y Xie, JM Renders, ... Proceedings of the 15th ACM Conference on Recommender Systems, 780-782, 2021.
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In 2020
11
Towards more practical adversarial attacks on graph neural networks. J Ma, S Ding, Q Mei Advances in neural information processing systems 33, 4756-4766, 2020.
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10
Off-policy learning in two-stage recommender systems. J Ma, Z Zhao, X Yi, J Yang, M Chen, J Tang, L Hong, EH Chi Proceedings of The Web Conference 2020, 463-473, 2020.
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9
Copulagnn: Towards integrating representational and correlational roles of graphs in graph neural networks. J Ma, B Chang, X Zhang, Q Mei arXiv preprint arXiv:2010.02089, 2020.
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8
Semi supervised joint learning for longitudinal clinical events classification using neural network models. W Tang, J Ma, AK Waljee, J Zhu Stat 9 (1), e305, 2020.
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In 2019
7
SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-task Learning. J Ma, Z Zhao, J Chen, A Li, L Hong, EH Chi .
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6
A flexible generative framework for graph-based semi-supervised learning. J Ma, W Tang, J Zhu, Q Mei Advances in Neural Information Processing Systems 32, 2019.
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5
Graph representation learning via multi-task knowledge distillation. J Ma, Q Mei arXiv preprint arXiv:1911.05700, 2019.
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In 2018
4
Modeling task relationships in multi-task learning with multi-gate mixture-of-experts. J Ma, Z Zhao, X Yi, J Chen, L Hong, EH Chi Proceedings of the 24th ACM SIGKDD international conference on knowledge ..., 2018.
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In 2017
3
Deepcas: An end-to-end predictor of information cascades. C Li, J Ma, X Guo, Q Mei Proceedings of the 26th international conference on World Wide Web, 577-586, 2017.
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In 2016
2
Joint community and structural hole spanner detection via harmonic modularity. L He, CT Lu, J Ma, J Cao, L Shen, PS Yu Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge ..., 2016.
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1
Learning cascaded influence under partial monitoring. J Zhang, J Ma, J Tang 2016 IEEE/ACM International Conference on Advances in Social Networks ..., 2016.
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