| Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective R Wei, H Yin, J Jia, AR Benson, P Li Advances in Neural Information Processing Systems (NeurIPS 2022), 2022 | 41 | 2022 |
| SLA P: Self-supervised Anomaly Detection with Adversarial Perturbation Y Wang, C Qin, R Wei, Y Xu, Y Bai, Y Fu IEEE Transactions on Knowledge and Data Engineering, 2022 | 21* | 2022 |
| Tedm-pu: A tax evasion detection method based on positive and unlabeled learning Y Wu, Q Zheng, Y Gao, B Dong, R Wei, F Zhang, H He 2019 IEEE international conference on big data (Big Data), 1681-1686, 2019 | 19 | 2019 |
| Unsupervised conditional adversarial networks for tax evasion detection R Wei, B Dong, Q Zheng, X Zhu, J Ruan, H He 2019 IEEE international conference on big data (Big Data), 1675-1680, 2019 | 15 | 2019 |
| Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models HP Wang, S Liu, R Wei, P Li International Conference on Machine Learning (ICML 25), 2025 | 9* | 2025 |
| A novel tax evasion detection framework via fused transaction network representation Y Wu, B Dong, Q Zheng, R Wei, Z Wang, X Li 2020 IEEE 44th Annual Computers, Software, and Applications Conference …, 2020 | 9 | 2020 |
| Differentially Private Graph Diffusion with Applications in Personalized PageRanks R Wei, E Chien, P Li Advances in Neural Information Processing Systems (NeurIPS 2024), 2024 | 8 | 2024 |
| On the inherent privacy properties of discrete denoising diffusion models R Wei, E Kreačić, H Wang, H Yin, E Chien, VK Potluru, P Li Transactions on Machine Learning Research 2024 (ICLR 25 Poster), 2024 | 8 | 2024 |
| Learning Scalable Structural Representations for Link Prediction with Bloom Signatures T Zhang, H Yin, R Wei, P Li, A Shrivastava 2024 Proceedings of the ACM Web Conference (WWW), 2023 | 7 | 2023 |
| ABR-HIC: attention based bidirectional RNN for hierarchical industry classification R Wei, Q Zheng, B Dong, K Yang, H He, J Ruan 2019 IEEE International Conference on Big Data (Big Data), 1527-1536, 2019 | 6 | 2019 |
| Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness R Wei, P Niu, HHH Hsu, R Wu, H Yin, M Ghassemi, Y Li, VK Potluru, ... Advances in Neural Information Processing Systems (NeurIPS 2025), 2025 | 4 | 2025 |
| NEUD-TRI: network embedding based on upstream and downstream for transaction risk identification J An, Q Zheng, R Wei, B Dong, X Li 2020 IEEE 44th Annual Computers, Software, and Applications Conference …, 2020 | 3 | 2020 |
| Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning R Wei, M Li, M Ghassemi, E Kreačić, Y Li, X Yue, B Li, VK Potluru, P Li, ... International Conference on Machine Learning (ICML 25), 2024 | 2 | 2024 |
| Guarding multiple secrets: Enhanced summary statistic privacy for data sharing S Wang, R Wei, M Ghassemi, E Kreacic, VK Potluru arXiv preprint arXiv:2405.13804, 2024 | 2 | 2024 |
| Privately Learning from Graphs with Applications in Fine-tuning Large Pretrained Models H Yin, R Wei, E Chien, P Li Conference on Language Modeling (COLM 2025), 2025 | 1* | 2025 |
| The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search R Wei, P Niu, X Shen, T Tu, Y Li, R Wu, E Chien, P Chen, O Milenkovic, ... arXiv preprint arXiv:2512.01353, 2025 | | 2025 |
| Towards Universal Debiasing for Language Models-based Tabular Data Generation T Li, T Liu, X Wang, R Wei, P Li, L Su, J Gao The 2025 Conference on Empirical Methods in Natural Language Processing …, 2025 | | 2025 |
| Differentially Private Relational Learning with Entity-level Privacy Guarantees Y Huang, H Yin, E Chien, R Wei, P Li Advances in Neural Information Processing Systems (NeurIPS 2025), 2025 | | 2025 |
Pan LiGeorgia Institute of Technology, Purdue UniversityVerified email at gatech.edu
