Tiejin Chen

According to our database, Tiejin Chen authored at least 21 papers between 2022 and 2026.

Collaborative distances:

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

2026

Are LLM Uncertainty and Correctness Encoded by the Same Features? A Functional Dissociation via Sparse Autoencoders.

Het Patel, Tiejin Chen, Hua Wei, Evangelos E. Papalexakis, Jia Chen

CoRR, April, 2026

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

CoRR, April, 2026

Zer0-Jack: A memory-efficient gradient-based jailbreaking method for black box Multi-modal Large Language Models.

Tiejin Chen, Kaishen Wang, Hua Wei

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment.

Tiejin Chen, Xiaoou Liu, Vishnu Nandam, Kuanru Liou, Hua Wei

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

2025

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

SIGKDD Explor., December, 2025

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

CoRR, July, 2025

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 Zhou, Ram Pendyala, Benjamin Stabler, Yezhou Yang, Xuesong Zhou, Hua Wei

CoRR, March, 2025

Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses.

Tiejin Chen, Xiaoou Liu, Longchao Da, Jia Chen, Vagelis Papalexakis, Hua Wei

CoRR, February, 2025

Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness.

Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei

Proceedings of the 2025 SIAM International Conference on Data Mining, 2025

Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey.

Xiaoou Liu, Tiejin Chen, Longchao Da, Chacha Chen, Zhen Lin, Hua Wei

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Reproducible and Low-cost Sim-to-Real Environment for Traffic Signal Control.

Yiran Zhang, Khoa Vo, Longchao Da, Tiejin Chen, Xiaoou Liu, Hua Wei

Proceedings of the ACM/IEEE 16th International Conference on Cyber-Physical Systems, 2025

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

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

Vision Language Model Helps Private Information De-Identification in Vision Data.

Tiejin Chen, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei

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

2024

Open-ti: open traffic intelligence with augmented language model.

Longchao Da, Kuanru Liou, Tiejin Chen, Xuesong Zhou, Xiangyong Luo, Yezhou Yang, Hua Wei

Int. J. Mach. Learn. Cybern., October, 2024

LLM Uncertainty Quantification through Directional Entailment Graph and Claim Level Response Augmentation.

Longchao Da, Tiejin Chen, Lu Cheng, Hua Wei

CoRR, 2024

Privacy-preserving Fine-tuning of Large Language Models through Flatness.

Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei

CoRR, 2024

When eBPF Meets Machine Learning: On-the-fly OS Kernel Compartmentalization.

Zicheng Wang, Tiejin Chen, Qinrun Dai, Yueqi Chen, Hua Wei, Qingkai Zeng

CoRR, 2024

SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras.

Tiejin Chen, Prithvi Shirke, Bharatesh Chakravarthi, Arpitsinh Vaghela, Longchao Da, Duo Lu, Yezhou Yang, Hua Wei

Proceedings of the 27th IEEE International Conference on Intelligent Transportation Systems, 2024

Uncertainty Regularized Evidential Regression.

Kai Ye, Tiejin Chen, Hua Wei, Liang Zhan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Federated Learning with Projected Trajectory Regularization.

Tiejin Chen, Yuanpu Cao, Yujia Wang, Cho-Jui Hsieh, Jinghui Chen

CoRR, 2023

2022

Learning Sparsity and Randomness for Data-driven Low Rank Approximation.

Tiejin Chen, Yicheng Tao

CoRR, 2022