Xun Xian

According to our database, Xun Xian authored at least 22 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science.

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

CoRR, March, 2026

RT2I-Bench: Evaluating Robustness of Text-to-Image Systems Against Adversarial Attacks.

Athanasios Glentis, Ioannis C. Tsaknakis, Jiangweizhi Peng, Xun Xian, Yihua Zhang, Gaowen Liu, Charles Fleming, Mingyi Hong

Trans. Mach. Learn. Res., 2026

2025

STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents.

Jing-Jing Li, Jianfeng He, Chao Shang, Devang Kulshreshtha, Xun Xian, Yi Zhang, Hang Su, Sandesh Swamy, Yanjun Qi

CoRR, September, 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, Zirui Liu, Mingyi Hong, Jie Ding

CoRR, May, 2025

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, May, 2025

On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains.

Xun Xian, Ganghua Wang, Xuan Bi, Rui Zhang, Jayanth Srinivasa, Ashish Kundu, Charles Fleming, Mingyi Hong, Jie Ding

Proceedings of the Forty-second International Conference on Machine Learning, 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, Charles Fleming, Mingyi Hong, Jie Ding

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Can Agentic AI Match the Performance of Human Data Scientists?

An Luo, Jin Du, Fangqiao Tian, Xun Xian, Robert Specht, Ganghua Wang, Xuan Bi, Charles Fleming, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding

Proceedings of the 10th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2025

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

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

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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Demystifying Poisoning Backdoor Attacks from a Statistical Perspective.

Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A Unified Detection Framework for Inference-Stage Backdoor Defenses.

Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Backdoor Attacks through the Adaptability Hypothesis.

Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

Proceedings of the International Conference on Machine Learning, 2023

2022

A Framework for Understanding Model Extraction Attack and Defense.

Xun Xian, Mingyi Hong, Jie Ding

CoRR, 2022

Understanding Model Extraction Games.

Xun Xian, Mingyi Hong, Jie Ding

Proceedings of the 4th IEEE International Conference on Trust, 2022

Mismatched Supervised Learning.

Xun Xian, Mingyi Hong, Jie Ding

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Assisted Learning: Cooperative AI with Autonomy.

Jiaying Zhou, Xun Xian, Na Li, Jie Ding

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

ASCII: ASsisted Classification with Ignorance Interchange.

Jiaying Zhou, Xun Xian, Na Li, Jie Ding

CoRR, 2020

Imitation Privacy.

Xun Xian, Xinran Wang, Mingyi Hong, Jie Ding, Reza Ghanadan

CoRR, 2020

Assisted Learning and Imitation Privacy.

Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan

CoRR, 2020

Assisted Learning: A Framework for Multi-Organization Learning.

Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020