| 2025 | CVPR | Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion. | Jiuhai Chen, Jianwei Yang, Haiping Wu, Dianqi Li, Jianfeng Gao, Tianyi Zhou, Bin Xiao |
| 2025 | NAACL | Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. | Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Taha A. Kass-Hout, Furong Huang, Cao Xiao |
| 2024 | ACL | Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness. | Jiuhai Chen, Jonas Mueller |
| 2024 | ACL | Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning. | Ming Li, Lichang Chen, Jiuhai Chen, Shwai He, Jiuxiang Gu, Tianyi Zhou |
| 2024 | ACL | Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements. | Ming Li, Jiuhai Chen, Lichang Chen, Tianyi Zhou |
| 2024 | ACL | Multi-Objective Linguistic Control of Large Language Models. | Dang Nguyen, Jiuhai Chen, Tianyi Zhou |
| 2024 | ICML | ODIN: Disentangled Reward Mitigates Hacking in RLHF. | Lichang Chen, Chen Zhu, Jiuhai Chen, Davit Soselia, Tianyi Zhou, Tom Goldstein, Heng Huang, Mohammad Shoeybi, Bryan Catanzaro |
| 2024 | ICML | InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models. | Lichang Chen, Jiuhai Chen, Tom Goldstein, Heng Huang, Tianyi Zhou |
| 2024 | NAACL | From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning. | Ming Li, Yong Zhang, Zhitao Li, Jiuhai Chen, Lichang Chen, Ning Cheng, Jianzong Wang, Tianyi Zhou, Jing Xiao |
| 2023 | EMNLP | PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. | Lichang Chen, Jiuhai Chen, Heng Huang, Minhao Cheng |
| 2023 | EMNLP | How Many Demonstrations Do You Need for In-context Learning? | Jiuhai Chen, Lichang Chen, Chen Zhu, Tianyi Zhou |
| 2023 | ICML | GOAT: A Global Transformer on Large-scale Graphs. | Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein |
| 2022 | ICLR | Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. | Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf |
| 2022 | ICLR | Why Propagate Alone? Parallel Use of Labels and Features on Graphs. | Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf |