| 2026 | ACL | Uncertainty Quantification of Large Language Models through Multiple Uncertainty Sources. | Tiejin Chen, Xiaoou Liu, Longchao Da, Jia Chen, Evangelos E. Papalexakis, Hua Wei |
| 2026 | ACL | 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 |
| 2026 | EACL | Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment. | Tiejin Chen, Xiaoou Liu, Vishnu Nandam, Kuanru Liou, Hua Wei |
| 2026 | EACL | Zer0-Jack: A memory-efficient gradient-based jailbreaking method for black box Multi-modal Large Language Models. | Tiejin Chen, Kaishen Wang, Hua Wei |
| 2025 | ACL | Vision Language Model Helps Private Information De-Identification in Vision Data. | Tiejin Chen, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei |
| 2025 | ACL | 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 |
| 2025 | KDD | Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey. | Xiaoou Liu, Tiejin Chen, Longchao Da, Chacha Chen, Zhen Lin, Hua Wei |
| 2025 | QCE | An Adaptive Weighted Qite-Vqe Algorithm for Combinatorial Optimization Problems. | Ningyi Xie, Xinwei Lee, Tiejin Chen, Yoshiyuki Saito, Nobuyoshi Asai, Dongsheng Cai |
| 2025 | SDM | 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 |
| 2024 | AAAI | Uncertainty Regularized Evidential Regression. | Kai Ye, Tiejin Chen, Hua Wei, Liang Zhan |