Towards a Secure Zero-rating Framework with Three Parties. - Zhiheng Liu; Zhen Zhang; Yinzhi Cao; Zhaohan Xi; Shihao Jing; Humberto J. La Roche (USENIX Security Symposium, 2018)

TROJANZOO: Everything you ever wanted to know about neural backdoors (but were afraid to ask). - Ren Pang; Zheng Zhang; Xiangshan Gao; Zhaohan Xi; Shouling Ji; Peng Cheng 001; Ting Wang 006 (CoRR, 2020)

Graph Backdoor. - Zhaohan Xi; Ren Pang; Shouling Ji; Ting Wang 006 (USENIX Security Symposium, 2021)

Towards Robust Reasoning over Knowledge Graphs. - Zhaohan Xi; Ren Pang; Changjiang Li; Shouling Ji; Xiapu Luo; Xusheng Xiao; Ting Wang 006 (CoRR, 2021)

TrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors. - Ren Pang; Zheng Zhang; Xiangshan Gao; Zhaohan Xi; Shouling Ji; Peng Cheng 001; Xiapu Luo; Ting Wang 006 (EuroS&P, 2022)

Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era. - Changjiang Li; Li Wang 120; Shouling Ji; Xuhong Zhang 002; Zhaohan Xi; Shanqing Guo; Ting Wang 006 (USENIX Security Symposium, 2022)

On the Security Risks of AutoML. - Ren Pang; Zhaohan Xi; Shouling Ji; Xiapu Luo; Ting Wang 006 (USENIX Security Symposium, 2022)

Reasoning over Multi-view Knowledge Graphs. - Zhaohan Xi; Ren Pang; Changjiang Li; Tianyu Du; Shouling Ji; Fenglong Ma; Ting Wang 006 (CoRR, 2022)

Demystifying Self-supervised Trojan Attacks. - Changjiang Li; Ren Pang; Zhaohan Xi; Tianyu Du; Shouling Ji; Yuan Yao 001; Ting Wang 006 (CoRR, 2022)

An Embarrassingly Simple Backdoor Attack on Self-supervised Learning. - Changjiang Li; Ren Pang; Zhaohan Xi; Tianyu Du; Shouling Ji; Yuan Yao 001; Ting Wang 006 (ICCV, 2023)

The Dark Side of AutoML: Towards Architectural Backdoor Search. - Ren Pang; Changjiang Li; Zhaohan Xi; Shouling Ji; Ting Wang 006 (ICLR, 2023)

Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks. - Zhaohan Xi; Tianyu Du; Changjiang Li; Ren Pang; Shouling Ji; Jinghui Chen; Fenglong Ma; Ting Wang 006 (NeurIPS, 2023)

On the Security Risks of Knowledge Graph Reasoning. - Zhaohan Xi; Tianyu Du; Changjiang Li; Ren Pang; Shouling Ji; Xiapu Luo; Xusheng Xiao; Fenglong Ma; Ting Wang 006 (USENIX Security Symposium, 2023)

PromptFix: Few-shot Backdoor Removal via Adversarial Prompt Tuning. - Tianrong Zhang; Zhaohan Xi; Ting Wang; Prasenjit Mitra; Jinghui Chen (NAACL-HLT, 2024)

On the Difficulty of Defending Contrastive Learning against Backdoor Attacks. - Changjiang Li; Ren Pang; Bochuan Cao; Zhaohan Xi; Jinghui Chen; Shouling Ji; Ting Wang 006 (USENIX Security Symposium, 2024)

Robustifying Safety-Aligned Large Language Models through Clean Data Curation. - Xiaoqun Liu; Jiacheng Liang; Muchao Ye; Zhaohan Xi (CoRR, 2024)

PromptFix: Few-shot Backdoor Removal via Adversarial Prompt Tuning. - Tianrong Zhang; Zhaohan Xi; Ting Wang 006; Prasenjit Mitra; Jinghui Chen (CoRR, 2024)

Zodiac: A Cardiologist-Level LLM Framework for Multi-Agent Diagnostics. - Yuan Zhou; Peng Zhang; Mengya Song; Alice Zheng; Yiwen Lu; Zhiheng Liu; Yong Chen 016; Zhaohan Xi (CoRR, 2024)

Buckle Up: Robustifying LLMs at Every Customization Stage via Data Curation. - Xiaoqun Liu; Jiacheng Liang; Luoxi Tang; Chenyu You; Muchao Ye; Zhaohan Xi (CoRR, 2024)

Cyber Defense Reinvented: Large Language Models as Threat Intelligence Copilots. - Xiaoqun Liu; Jiacheng Liang; Qiben Yan; Muchao Ye; Jinyuan Jia; Zhaohan Xi (CoRR, 2025)

All Your Knowledge Belongs to Us: Stealing Knowledge Graphs via Reasoning APIs. - Zhaohan Xi (CoRR, 2025)

On the Eligibility of LLMs for Counterfactual Reasoning: A Decompositional Study. - Shuai Yang; Qi Yang; Luoxi Tang; Jeremy Blackburn; Zhaohan Xi (CoRR, 2025)

Benchmarking LLMs in an Embodied Environment for Blue Team Threat Hunting. - Xiaoqun Liu; Feiyang Yu; Xi Li; Guanhua Yan; Ping Yang; Zhaohan Xi (CoRR, 2025)

Are LLMs Ready for English Standardized Tests? A Benchmarking and Elicitation Perspective. - Luoxi Tang; Tharunya Sundar; Shuai Yang; Ankita Patra; Manohar Chippada; Giqi Zhao; Yi Li; Riteng Zhang; Tunan Zhao; Ting Yang; Yuqiao Meng; Weicheng Ma; et al. (CoRR, 2025)