Ganghua Wang - RankMe

27 papers A* 6Journal 19Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science. CoRR An Luo, Jin Du, Xun Xian, Robert Specht, Fangqiao Tian, Ganghua Wang, Xuan Bi, Charles Fleming, Ashish Kundu, Jayanth Srinivasa, Mingyi Hong, Rui Zhang, Tianxi Li, Galin Jones, Jie Ding
2025	J	`jnl`	An Outlook on the Opportunities and Challenges of Multi-Agent AI Systems. CoRR Fangqiao Tian, An Luo, Jin Du, Xun Xian, Robert Specht, Ganghua Wang, Xuan Bi, Jiawei Zhou, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Rui Zhang, Zirui Liu, Mingyi Hong, Jie Ding
2025	—	`conf`	AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science. EMNLP (Findings) An Luo, Xun Xian, Jin Du, Fangqiao Tian, Ganghua Wang, Ming Zhong, Shengchun Zhao, Xuan Bi, Zirui Liu, Jiawei Zhou, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding
2025	J	`jnl`	AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science. CoRR An Luo, Xun Xian, Jin Du, Fangqiao Tian, Ganghua Wang, Ming Zhong, Shengchun Zhao, Xuan Bi, Zirui Liu, Jiawei Zhou, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding
2025	—	`conf`	Can Agentic AI Match the Performance of Human Data Scientists? CAMSAP An Luo, Jin Du, Fangqiao Tian, Xun Xian, Robert Specht, Ganghua Wang, Xuan Bi, Charles Fleming, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding
2025	J	`jnl`	Can Agentic AI Match the Performance of Human Data Scientists? CoRR An Luo, Jin Du, Fangqiao Tian, Xun Xian, Robert Specht, Ganghua Wang, Xuan Bi, Charles Fleming, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding
2025	J	`jnl`	Cer-Eval: Certifiable and Cost-Efficient Evaluation Framework for LLMs. CoRR Ganghua Wang, Zhaorun Chen, Bo Li, Haifeng Xu
2025	J	`jnl`	Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference. CoRR Jin Du, Li Chen, Xun Xian, An Luo, Fangqiao Tian, Ganghua Wang, Charles Doss, Xiaotong Shen, Jie Ding
2025	J	`jnl`	Model Privacy: A Unified Framework to Understand Model Stealing Attacks and Defenses. CoRR Ganghua Wang, Yuhong Yang, Jie Ding
2025	A*	`conf`	On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains. ICML Xun Xian, Ganghua Wang, Xuan Bi, Rui Zhang, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding
2024	A*	`conf`	Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. ICLR Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding
2024	J	`jnl`	Drift to Remember. CoRR Jin Du, Xinhe Zhang, Hao Shen, Xun Xian, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Na Li, Jia Liu, Jie Ding
2024	J	`jnl`	Mitigating Group Bias in Federated Learning: Beyond Local Fairness. Trans. Mach. Learn. Res. Ganghua Wang, Ali Payani, Myungjin Lee, Ramana Rao Kompella
2024	J	`jnl`	On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains. CoRR Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding
2024	A*	`conf`	RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees. NeurIPS Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding
2024	J	`jnl`	RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees. CoRR Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding
2023	A*	`conf`	A Unified Detection Framework for Inference-Stage Backdoor Defenses. NeurIPS Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
2023	J	`jnl`	Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. CoRR Ganghua Wang, Xun Xian, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
2023	J	`jnl`	Mitigating Group Bias in Federated Learning: Beyond Local Fairness. CoRR Ganghua Wang, Ali Payani, Myungjin Lee, Ramana Kompella
2023	J	`jnl`	Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization. CoRR Gen Li, Ganghua Wang, Jie Ding
2023	J	`jnl`	Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization. IEEE Trans. Inf. Theory Gen Li, Ganghua Wang, Jie Ding
2023	A*	`conf`	Pruning Deep Neural Networks from a Sparsity Perspective. ICLR Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
2023	J	`jnl`	Pruning Deep Neural Networks from a Sparsity Perspective. CoRR Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
2023	A*	`conf`	Understanding Backdoor Attacks through the Adaptability Hypothesis. ICML Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
2022	J	`jnl`	A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation. CoRR Wenjing Yang, Ganghua Wang, Enmao Diao, Vahid Tarokh, Jie Ding, Yuhong Yang
2021	J	`jnl`	Subset Privacy: Draw from an Obfuscated Urn. CoRR Ganghua Wang, Jie Ding
2017	J	`jnl`	Error estimates on a finite volume method for diffusion problems with interface on rectangular grids. Appl. Math. Comput. Jie Peng, Shi Shu, Haiyuan Yu, Chunsheng Feng, Mingxian Kan, Ganghua Wang