Publications

* Equal Contribution

Under Review / arXiv

• [arXiv] Yukun Jiang, Yage Zhang, Michael Backes, Xinyue Shen, Yang Zhang: ‘‘HarmfulSkillBench: How Do Harmful Skills Weaponize Your Agents?’’ [arXiv] [Code] [Dataset]
• [arXiv] Yukun Jiang*, Yage Zhang*, Xinyue Shen*, Michael Backes, Yang Zhang: ‘‘“Humans welcome to observe”: A First Look at the Agent Social Network Moltbook.’’ [Website] [PDF] [Dataset] [arXiv] Media Coverage: [TechXplore] [AI Era (Chinese)]
• [arXiv] Yichuan Mo*, Yukun Jiang*, Yanbo Shi*, Mingjie Li*, Michael Backes, Yang Zhang, Yisen Wang: ‘‘TrustLDM: Benchmarking Trustworthiness in Language Diffusion Models.’’ [arXiv]
• [arXiv] Mengfei Liang, Yiting Qu, Yukun Jiang, Michael Backes, Yang Zhang: ‘‘From Evidence to Verdict: An Agent-Based Forensic Framework for AI-Generated Image Detection.’’ [arXiv]

Conference / Journal

• [CCS 2026] Yage Zhang*, Yukun Jiang*, Zeyuan Chen, Michael Backes, Xinyue Shen, Yang Zhang: ‘‘Real Money, Fake Models: Deceptive Model Claims in Shadow APIs.’’ [arXiv] Media Coverage: [JIQIZHIXIN | Synced (Chinese)]
• [CCS 2026] Yage Zhang, Xinyue Shen, Yukun Jiang, Michael Backes, Yang Zhang: ‘‘“Shut Up and Let Me Enjoy My Otome”: Understanding and Measuring the Toxicity in Otome Game Communities.’’ [arXiv]
• [ICML 2026] Yukun Jiang, Hai Huang, Mingjie Li, Yage Zhang, Michael Backes, Yang Zhang: ‘‘Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs.’’ [arXiv] [Code]
• [ACL 2026] Yukun Jiang, Xinyue Shen, Michael Backes, Zheng Li, Yang Zhang: ‘‘Open Schrödinger’s Closed Box: Identifying Retrieval Augmented Generation in API-Accessible Large Language Model Services.’’
• [ACL 2026] Yage Zhang, Yukun Jiang, Michael Backes, Yang Zhang: ‘‘DE-CLIP: Few-Shot Anomaly Detection via Difference-Guided Embedding Editing.’’
• [NeurIPS 2025] Yukun Jiang, Mingjie Li, Michael Backes, Yang Zhang: ‘‘Adjacent Words, Divergent Intents: Jailbreaking Large Language Models via Task Concurrency.’’ [PDF] [Link] [Code]
• [EMNLP 2024] Yukun Jiang, Zheng Li, Xinyue Shen, Yugeng Liu, Michael Backes, Yang Zhang: ‘‘ModSCAN: Measuring Stereotypical Bias in Large Vision-Language Models from Vision and Language Modalities.’’ [PDF] [Link] [Code]
• [ICWSM 2024] Yukun Jiang, Xinyue Shen, Rui Wen, Zeyang Sha, Junjie Chu, Yugeng Liu, Michael Backes, Yang Zhang: ‘‘Games and Beyond: Analyzing the Bullet Chats of Esports Livestreaming.’’ [PDF] [Link]
• [T-ITS 2022] Beibei Li, Yukun Jiang, Qingqi Pei, Tao Li, Liang Liu, Rongxing Lu: ‘‘FEEL: Federated End-to-End Learning with Non-IID Data for Vehicular Ad Hoc Networks.’’ [Link]
• [ICLR-W 2022] Yukun Jiang, Xiaoyu Cao, Hao Chen, Neil Gong: ‘‘FedER: Communication-Efficient Byzantine-Robust Federated Learning.’’ [PDF]
• [INFOCOM-W 2022] Beibei Li, Yaxin Shi, Yuqing Guo, Qinglei Kong, Yukun Jiang: ‘‘Incentive-Based Adaptive Federated Knowledge Distillation for Cross-Silo Applications.’’ [PDF]
• [GLOBECOM 2021] Beibei Li, Yukun Jiang, Wenbin Sun, Weina Niu, Peiran Wang: ‘‘FedVANET: Efficient Federated Learning with Non-IID Data for Vehicular Ad Hoc Networks.’’ [Link] [PDF]
• [ISCC 2021] Beibei Li, Peiran Wang, Hanyuan Huang, Shang Ma, Yukun Jiang: ‘‘FLPhish: Reputation-Based Phishing Byzantine Defense in Ensemble Federated Learning.’’ Best Paper Award [Link] [PDF]

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