Xun Xian - RankMe

26 papers A* 6Misc 2Journal 15Unranked 3

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
2026	J	`jnl`	RT2I-Bench: Evaluating Robustness of Text-to-Image Systems Against Adversarial Attacks. Trans. Mach. Learn. Res. Athanasios Glentis, Ioannis C. Tsaknakis, Jiangweizhi Peng, Xun Xian, Yihua Zhang, Gaowen Liu, Charles Fleming, Mingyi Hong
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`	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	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
2025	J	`jnl`	STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents. CoRR Jing-Jing Li, Jianfeng He, Chao Shang, Devang Kulshreshtha, Xun Xian, Yi Zhang, Hang Su, Sandesh Swamy, Yanjun Qi
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`	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	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 Framework for Understanding Model Extraction Attack and Defense. CoRR Xun Xian, Mingyi Hong, Jie Ding
2022	Misc	`conf`	Mismatched Supervised Learning. ICASSP Xun Xian, Mingyi Hong, Jie Ding
2022	—	`conf`	Understanding Model Extraction Games. TPS-ISA Xun Xian, Mingyi Hong, Jie Ding
2021	Misc	`conf`	Assisted Learning: Cooperative AI with Autonomy. ICASSP Jiaying Zhou, Xun Xian, Na Li, Jie Ding
2020	J	`jnl`	ASCII: ASsisted Classification with Ignorance Interchange. CoRR Jiaying Zhou, Xun Xian, Na Li, Jie Ding
2020	J	`jnl`	Assisted Learning and Imitation Privacy. CoRR Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan
2020	A*	`conf`	Assisted Learning: A Framework for Multi-Organization Learning. NeurIPS Xun Xian, Xinran Wang, Jie Ding, Reza Ghanadan
2020	J	`jnl`	Imitation Privacy. CoRR Xun Xian, Xinran Wang, Mingyi Hong, Jie Ding, Reza Ghanadan