Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference - Jin Du; Li Chen; Xun Xian; An Luo; Fangqiao Tian; Ganghua Wang; Charles Doss; Xiaotong Shen; Jie Ding (CoRR, 2025)

An Outlook on the Opportunities and Challenges of Multi-Agent AI Systems - Fangqiao Tian; An Luo; Jin Du; Xun Xian; Robert Specht; Ganghua Wang; Xuan Bi; Jiawei Zhou; Jayanth Srinivasa; Ashish Kundu; Charles Fleming; Rui Zhang; et al. (CoRR, 2025)

AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science - An Luo; Xun Xian; Jin Du; Fangqiao Tian; Ganghua Wang; Ming Zhong; Shengchun Zhao; Xuan Bi; Zirui Liu; Jiawei Zhou; Jayanth Srinivasa; Ashish Kundu; et al. (CoRR, 2025)

Demystifying Poisoning Backdoor Attacks from a Statistical Perspective - Ganghua Wang; Xun Xian; Ashish Kundu; Jayanth Srinivasa; Xuan Bi; Mingyi Hong; Jie Ding (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees - Xun Xian; Ganghua Wang; Xuan Bi; Jayanth Srinivasa; Ashish Kundu; Mingyi Hong; Jie Ding (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees - Xun Xian; Ganghua Wang; Xuan Bi; Jayanth Srinivasa; Ashish Kundu; Mingyi Hong; Jie Ding (CoRR, 2024)

Drift to Remember - Jin Du; Xinhe Zhang; Hao Shen; Xun Xian; Ganghua Wang; Jiawei Zhang; Yuhong Yang; Na Li; Jia Liu; Jie Ding (CoRR, 2024)

On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains - Xun Xian; Ganghua Wang; Xuan Bi; Jayanth Srinivasa; Ashish Kundu; Charles Fleming; Mingyi Hong; Jie Ding (CoRR, 2024)

Understanding Backdoor Attacks through the Adaptability Hypothesis - Xun Xian; Ganghua Wang; Jayanth Srinivasa; Ashish Kundu; Xuan Bi; Mingyi Hong; Jie Ding (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

A Unified Detection Framework for Inference-Stage Backdoor Defenses - Xun Xian; Ganghua Wang; Jayanth Srinivasa; Ashish Kundu; Xuan Bi; Mingyi Hong; Jie Ding (Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023)

Demystifying Poisoning Backdoor Attacks from a Statistical Perspective - Ganghua Wang; Xun Xian; Jayanth Srinivasa; Ashish Kundu; Xuan Bi; Mingyi Hong; Jie Ding (CoRR, 2023)

Mismatched Supervised Learning - Xun Xian; Mingyi Hong; Jie Ding (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022, Virtual and Singapore, 23-27 May 2022, 2022)

Understanding Model Extraction Games - Xun Xian; Mingyi Hong; Jie Ding (4th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, TPS-ISA 2022, Atlanta, GA, USA, December 14-17, 2022, 2022)

A Framework for Understanding Model Extraction Attack and Defense - Xun Xian; Mingyi Hong; Jie Ding (CoRR, 2022)

Assisted Learning: Cooperative AI with Autonomy - Jiaying Zhou; Xun Xian; Na Li; Jie Ding (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2021, Toronto, ON, Canada, June 6-11, 2021, 2021)

Assisted Learning: A Framework for Multi-Organization Learning - Xun Xian; Xinran Wang; Jie Ding; Reza Ghanadan (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Assisted Learning and Imitation Privacy - Xun Xian; Xinran Wang; Jie Ding; Reza Ghanadan (CoRR, 2020)

Imitation Privacy - Xun Xian; Xinran Wang; Mingyi Hong; Jie Ding; Reza Ghanadan (CoRR, 2020)

ASCII: ASsisted Classification with Ignorance Interchange - Jiaying Zhou; Xun Xian; Na Li; Jie Ding (CoRR, 2020)