Tiejin Chen

According to our database, Tiejin Chen authored at least 10 papers between 2022 and 2024.

Collaborative distances:

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

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

Zer0-Jack: A Memory-efficient Gradient-based Jailbreaking Method for Black-box Multi-modal Large Language Models.

Tiejin Chen, Kaishen Wang, Hua Wei

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

CoRR, 2024

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

Longchao Da, Tiejin Chen, Lu Cheng, Hua Wei

CoRR, 2024

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

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

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