Lastest Update: 06/09/2026 

Preprints

• Generative AI in Transportation Planning: A Survey
  Longchao Da, Tiejin Chen, Zhuoheng Li, Shreyas Bachiraju, Huaiyuan Yao, Li Li, Yushun Dong, Xiyang Hu, Zhengzhong Tu, Dongjie Wang, Yue Zhao, Xuanyu (Ben)Zhou, Ram Pendyala, Benjamin Stabler, Yezhou Yang, Xuesong Zhou, Hua Wei
  

• LLM Uncertainty Quantification through Directional Entailment Graph and Claim Level Response Augmentation
  Longchao Da, Tiejin Chen, Lu Cheng, Hua Wei
  

• Learning Sparsity and Randomness for Data-driven Low Rank Approximation
  Tiejin Chen^*, Yicheng Tao^*
  

Conference Paper

• The Sim-to-Real Gap of Foundation Model Agents: A Unified MDP Perspective
  Tiejin Chen^*, Xiaoou Liu^*, Weibo Li，Xiyang Hu, Hua Wei
  In Proceedings of the 32nd ACM SIGKDD international conference on Knowledge discovery and data mining - Blue Sky Track (KDD’ 26)
  

• Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
  Tiejin Chen, Longchao Da, Xiaoou Liu, Hua Wei
  Forty-Third International Conference on Machine Learning - Position Track (ICML’ 26)
  

• Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
  Xiaoou Liu, Tiejin Chen, Dengjia Zhang, Yaqing Wang, Lu Cheng, Hua Wei
  Forty-Third International Conference on Machine Learning (ICML’ 26)
  

• Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition
  Tiejin Chen, Huaiyuan Yao, Jia Chen, Evangelos E. Papalexakis, Hua Wei
  The 64th Annual Meeting of the Association for Computational Linguistics (ACL’26 Main)
  

• Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses
  Tiejin Chen, Xiaoou Liu, Longchao Da, Jia Chen, Vagelis Papalexakis, Hua Wei
  Findings of the Association for Computational Linguistics ACL 2026 (ACL’26 Findings)

• Agentic AI for Trip Planning Optimization Application
  Tiejin Chen, Ahmadreza Moradipari, Kyungtae Han, Hua Wei, Nejib Ammar
  The IEEE Intelligent Vehicles Symposium (IV) 2026
  

• Zer0-Jack: A Memory-efficient Gradient-based Jailbreaking Method for Black-box Multi-modal Large Language Models
  Tiejin Chen^*, Kaishen Wang^*, Hua Wei
  The 19th Conference of the European Chapter of the Association for Computational Linguistics (Oral at EACL 2026 Main), Also Present at GenSafeAI Workshop @ Neurips 2024
  

• Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment
  Tiejin Chen, Xiaoou Liu, Vishnu Nandam, Kuan-Ru Liou, Hua Wei
  Findings of The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026 Findings)
  

• Joint-Local Grounded Action Transformation for Sim-to-Real Transfer in Multi-Agent Traffic Control
  Justin Turnau, Longchao Da, Khoa Vo, Ferdous Al Rafi, Shreyas Bachiraju, Tiejin Chen, Hua Wei
  Reinforcement Learning Conference (RLC) 2025
  

• An Adaptive Weighted QITE-VQE Algorithm for Combinatorial Optimization Problems
  Ningyi Xie, Xinwei Lee, Tiejin Chen, Yoshiyuki Saito, Nobuyoshi Asai, Dongsheng Cai
  2025 IEEE International Conference on Quantum Computing and Engineering (QCE)

• Vision Language Model Helps Private Information De-Identification in Vision Data
  Tiejin Chen, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei.
  Findings of the Association for Computational Linguistics ACL 2025 (ACL’25 Findings)
  

• Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges
  Tiejin Chen, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei.
  Findings of the Association for Computational Linguistics ACL 2025 (ACL’25 Findings)
  

• Reproducible and Low-cost Sim-to-Real Environment for Traffic Signal Control
  Yiran Zhang, Khoa Vo, Longchao Da, Tiejin Chen, Xiaoou Liu, Hua Wei
  ACM/IEEE 16th International Conference on Cyber-Physical Systems (ICCPS 2025)
  

• Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey
  Tiejin Chen^*, Xiaoou Liu^*, Longchao Da, Chacha Chen, Zhen Lin, Hua Wei
  In the Proceedings of the 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’25)
  

• Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness
  Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaizhong Zhou, Tianlong Chen, Hua Wei
  In SIAM International Conference on Data Mining (SDM’25). (Short version presented at ICLR 2024 Workshop on Secure and Trustworthy Large Language Models)
  

• Abg-SciQA: A dataset for Understanding and Resolving Ambiguity in Scientific Questions
  Tiejin Chen^*, Kuan-Ru Liou^*, Mithun Shivakoti, Aaryan Gaur, Pragya Kumari, Meiqi Guo, Hua Wei
  ICLR 2025 Workshop on Navigating and Addressing Data Problems for Foundation Models
  

• SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras
  Tiejin Chen^*, Prithvi Parag Shirke^*, Bharatesh Chakravarthi, Arpitsinh Rohitkumar Vaghela, Longchao Da, Duo Lu, Yezhou Yang, Hua Wei
  In Proceedings of 27th IEEE International Conference on Intelligent Transportation Systems (ITSC’24).
  

• Uncertainty Regularized Evidential Regression
  Kai Ye, Tiejin Chen, Hua Wei, Liang Zhan
  In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI’24).
  

• When eBPF Meets Machine Learning: On-the-fly OS Kernel Compartmentalization
  Zicheng Wang, Tiejin Chen, Qinrun Dai, Yueqi Chen, Hua Wei, Qingkai Zeng
  BlackHat USA 2024 Briefing.
  

Journal Paper

• Federated Learning with Projected Trajectory Regularization
  Tiejin Chen^*, Yuanpu Cao^*, Yujia Wang^*, Cho-Jui Hsieh, Jinghui Chen
  Transactions on Machine Learning Research (TMLR).
  

• Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
  Tiejin Chen, Wenwang Huang, Linsey Pang, Dongsheng Luo, Hua Wei
  ACM SIGKDD Explorations Newsletter.
  

• Open-TI: Open Traffic Intelligence with Augmented Language Model
  Longchao Da, Kuanru Liou, Tiejin Chen, Xuesong Zhou, Xiangyong Luo, Yezhou Yang, Huawei
  International Journal of Machine Learning and Cybernetics.
  

• Performance Upper Bound of the Grover-Mixer Quantum Alternating Operator Ansatz
  Ningyi Xie, Jiahua Xu, Tiejin Chen, Yoshiyuki Saito, Nobuyoshi Asai, Dongsheng Cai
  Physical Review A.
  

• Prison term prediction of dangerous driving based on probabilistic graphical mode
  Chen Hongxu, Chen Tiejin, Wang Hao, Tian Wei
  Journal of Sichuan University（Natural Science Edition）
  

Working Manuscript

One unpublic papser is under review of ARR March Round. One unpublic papser is under review of ARR May Round. One unpublic papser is under review of NeurIPS 2026.