Rongzhe Wei - RankMe

31 papers A* 5A 1B 3Journal 18Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GRIP: Algorithm-Agnostic Machine Unlearning for Mixture-of-Experts via Geometric Router Constraints. CoRR Andy Zhu, Rongzhe Wei, Yupu Gu, Pan Li
2026	J	`jnl`	MoEEdit: Efficient and Routing-Stable Knowledge Editing for Mixture-of-Experts LLMs. CoRR Yupu Gu, Rongzhe Wei, Andy Zhu, Pan Li
2025	J	`jnl`	Differentially Private Relational Learning with Entity-level Privacy Guarantees. CoRR Yinan Huang, Haoteng Yin, Eli Chien, Rongzhe Wei, Pan Li
2025	J	`jnl`	Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness. CoRR Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K. Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li
2025	A*	`conf`	Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models. ICML Haoyu Peter Wang, Shikun Liu, Rongzhe Wei, Pan Li
2025	J	`jnl`	Model Generalization on Text Attribute Graphs: Principles with Large Language Models. CoRR Haoyu Wang, Shikun Liu, Rongzhe Wei, Pan Li
2025	J	`jnl`	The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search. CoRR Rongzhe Wei, Peizhi Niu, Xinjie Shen, Tony Tu, Yifan Li, Ruihan Wu, Eli Chien, Pin-Yu Chen, Olgica Milenkovic, Pan Li
2025	—	`conf`	Towards Universal Debiasing for Language Models-based Tabular Data Generation. EMNLP (Findings) Tianchun Li, Tianci Liu, Xingchen Wang, Rongzhe Wei, Pan Li, Lu Su, Jing Gao
2025	J	`jnl`	Towards Universal Debiasing for Language Models-based Tabular Data Generation. CoRR Tianchun Li, Tianci Liu, Xingchen Wang, Rongzhe Wei, Pan Li, Lu Su, Jing Gao
2025	A*	`conf`	Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. ICML Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien
2024	A*	`conf`	Differentially Private Graph Diffusion with Applications in Personalized PageRanks. NeurIPS Rongzhe Wei, Eli Chien, Pan Li
2024	J	`jnl`	Differentially Private Graph Diffusion with Applications in Personalized PageRanks. CoRR Rongzhe Wei, Eli Chien, Pan Li
2024	J	`jnl`	Guarding Multiple Secrets: Enhanced Summary Statistic Privacy for Data Sharing. CoRR Shuaiqi Wang, Rongzhe Wei, Mohsen Ghassemi, Eleonora Kreacic, Vamsi K. Potluru
2024	A*	`conf`	Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
2024	J	`jnl`	On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. Trans. Mach. Learn. Res. Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
2024	J	`jnl`	Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. CoRR Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li
2024	J	`jnl`	SLA$^{{\text{2}}}$2P: Self-Supervised Anomaly Detection With Adversarial Perturbation. IEEE Trans. Knowl. Data Eng. Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu
2024	J	`jnl`	Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. CoRR Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien
2023	J	`jnl`	Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
2023	J	`jnl`	On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. CoRR Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
2022	A	`conf`	Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection. CIKM Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu
2022	A*	`conf`	Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. NeurIPS Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
2022	J	`jnl`	Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. CoRR Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
2021	J	`jnl`	SLA CoRR Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu
2020	B	`conf`	A Novel Tax Evasion Detection Framework via Fused Transaction Network Representation. COMPSAC Yingchao Wu, Bo Dong, Qinghua Zheng, Rongzhe Wei, Zhiwen Wang, Xuanya Li
2020	J	`jnl`	DWMD: Dimensional Weighted Orderwise Moment Discrepancy for Domain-specific Hidden Representation Matching. CoRR Rongzhe Wei, Fa Zhang, Bo Dong, Qinghua Zheng
2020	B	`conf`	Dual Adversarial Networks for Land-Cover Classification. COMPSAC Jingyi An, Rongzhe Wei, Zhichao Zha, Bo Dong
2020	B	`conf`	NEUD-TRI: Network Embedding Based on Upstream and Downstream for Transaction Risk Identification. COMPSAC Jingyi An, Qinghua Zheng, Rongzhe Wei, Bo Dong, Xuanya Li
2019	—	`conf`	ABR-HIC: Attention Based Bidirectional RNN for Hierarchical Industry Classification. IEEE BigData Rongzhe Wei, Qinghua Zheng, Bo Dong, Kuanzheng Yang, Huan He, Jianfei Ruan
2019	—	`conf`	TEDM-PU: A Tax Evasion Detection Method Based on Positive and Unlabeled Learning. IEEE BigData Yingchao Wu, Qinghua Zheng, Yuda Gao, Bo Dong, Rongzhe Wei, Fa Zhang, Huan He
2019	—	`conf`	Unsupervised Conditional Adversarial Networks for Tax Evasion Detection. IEEE BigData Rongzhe Wei, Bo Dong, Qinghua Zheng, Xulyu Zhu, Jianfei Ruan, Huan He