Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features. - Jiuhai Chen; Jonas Mueller 001; Vassilis N. Ioannidis; Soji Adeshina; Yangkun Wang; Tom Goldstein; David Wipf (CoRR, 2021)

Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task. - Jiuhai Chen; Chen Zhu; Bin Dai (CoRR, 2021)

Particle-based energetic variational inference. - Yiwei Wang; Jiuhai Chen; Chun Liu 009; Lulu Kang (Stat. Comput., 2021)

Gaussian Process Assisted Active Learning of Physical Laws. - Jiuhai Chen; Lulu Kang; Guang Lin 001 (Technometrics, 2021)

Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. - Jiuhai Chen; Jonas Mueller 001; Vassilis N. Ioannidis; Soji Adeshina; Yangkun Wang; Tom Goldstein; David Wipf (ICLR, 2022)

Why Propagate Alone? Parallel Use of Labels and Features on Graphs. - Yangkun Wang; Jiarui Jin; Weinan Zhang 001; Yongyi Yang; Jiuhai Chen; Quan Gan; Yong Yu 001; Zheng Zhang 001; Zengfeng Huang; David Wipf (ICLR, 2022)

A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features. - Jiuhai Chen; Jonas Mueller 001; Vassilis N. Ioannidis; Tom Goldstein; David Wipf (CoRR, 2022)

PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. - Lichang Chen; Jiuhai Chen; Heng Huang; Minhao Cheng (EMNLP, 2023)

How Many Demonstrations Do You Need for In-context Learning? - Jiuhai Chen; Lichang Chen; Chen Zhu 001; Tianyi Zhou 001 (EMNLP (Findings), 2023)

GOAT: A Global Transformer on Large-scale Graphs. - Kezhi Kong; Jiuhai Chen; John Kirchenbauer; Renkun Ni; C. Bayan Bruss; Tom Goldstein (ICML, 2023)

It Takes One to Tango but More Make Trouble? The Number of Demonstrations Needed for In-Context Learning. - Jiuhai Chen; Lichang Chen; Chen Zhu 001; Tianyi Zhou 001 (CoRR, 2023)

When do you need Chain-of-Thought Prompting for ChatGPT? - Jiuhai Chen; Lichang Chen; Heng Huang; Tianyi Zhou 001 (CoRR, 2023)

Quantifying Uncertainty in Answers from any Language Model via Intrinsic and Extrinsic Confidence Assessment. - Jiuhai Chen; Jonas Mueller 001 (CoRR, 2023)

Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning. - Ming Li; Lichang Chen; Jiuhai Chen; Shwai He; Heng Huang; Jiuxiang Gu; Tianyi Zhou 001 (CoRR, 2023)

Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness. - Jiuhai Chen; Jonas Mueller 001 (ACL (1), 2024)

Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning. - Ming Li; Lichang Chen; Jiuhai Chen; Shwai He; Jiuxiang Gu; Tianyi Zhou 001 (ACL (Findings), 2024)

Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements. - Ming Li; Jiuhai Chen; Lichang Chen; Tianyi Zhou 001 (ACL (Findings), 2024)

Multi-Objective Linguistic Control of Large Language Models. - Dang Nguyen; Jiuhai Chen; Tianyi Zhou 001 (ACL (Findings), 2024)

ODIN: Disentangled Reward Mitigates Hacking in RLHF. - Lichang Chen; Chen Zhu 001; Jiuhai Chen; Davit Soselia; Tianyi Zhou 001; Tom Goldstein; Heng Huang; Mohammad Shoeybi; Bryan Catanzaro (ICML, 2024)

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models. - Lichang Chen; Jiuhai Chen; Tom Goldstein; Heng Huang; Tianyi Zhou 001 (ICML, 2024)

From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning. - Ming Li; Yong Zhang 058; Zhitao Li 002; Jiuhai Chen; Lichang Chen; Ning Cheng 001; Jianzong Wang; Tianyi Zhou 001; Jing Xiao 006 (NAACL-HLT, 2024)

Automated Data Curation for Robust Language Model Fine-Tuning. - Jiuhai Chen; Jonas Mueller 001 (CoRR, 2024)

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. - Xiyao Wang; Jiuhai Chen; Zhaoyang Wang 004; Yuhang Zhou; Yiyang Zhou; Huaxiu Yao; Tianyi Zhou 001; Tom Goldstein; Parminder Bhatia; Furong Huang; Cao Xiao (CoRR, 2024)

OPTune: Efficient Online Preference Tuning. - Lichang Chen; Jiuhai Chen; Chenxi Liu; John Kirchenbauer; Davit Soselia; Chen Zhu 001; Tom Goldstein; Tianyi Zhou 001; Heng Huang (CoRR, 2024)

GenQA: Generating Millions of Instructions from a Handful of Prompts. - Jiuhai Chen; Rifaa Qadri; Yuxin Wen; Neel Jain; John Kirchenbauer; Tianyi Zhou 001; Tom Goldstein (CoRR, 2024)

Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models. - Jiuhai Chen; Jonas Mueller 001; Vassilis N. Ioannidis; Tom Goldstein; David Wipf (Trans. Mach. Learn. Res., 2024)

Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion. - Jiuhai Chen; Jianwei Yang; Haiping Wu; Dianqi Li; Jianfeng Gao 001; Tianyi Zhou 001; Bin Xiao 004 (CVPR, 2025)

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. - Xiyao Wang; Jiuhai Chen; Zhaoyang Wang 004; Yuhang Zhou; Yiyang Zhou; Huaxiu Yao; Tianyi Zhou 001; Tom Goldstein; Parminder Bhatia; Taha A. Kass-Hout; Furong Huang; Cao Xiao (NAACL (Findings), 2025)

Transfer between Modalities with MetaQueries. - Xichen Pan; Satya Narayan Shukla; Aashu Singh; Zhuokai Zhao; Shlok Kumar Mishra; Jialiang Wang 001; Zhiyang Xu; Jiuhai Chen; Kunpeng Li; Felix Juefei-Xu; Ji Hou; Saining Xie (CoRR, 2025)

ColorBench: Can VLMs See and Understand the Colorful World? A Comprehensive Benchmark for Color Perception, Reasoning, and Robustness. - Yijun Liang; Ming Li; Chenrui Fan; Ziyue Li; Dang Nguyen; Kwesi Cobbina; Shweta Bhardwaj; Jiuhai Chen; Fuxiao Liu; Tianyi Zhou 001 (CoRR, 2025)

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset. - Jiuhai Chen; Zhiyang Xu; Xichen Pan; Yushi Hu; Can Qin; Tom Goldstein; Lifu Huang; Tianyi Zhou 001; Saining Xie; Silvio Savarese; Le Xue; Caiming Xiong; et al. (CoRR, 2025)

LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer. - Ying Shen 006; Zhiyang Xu; Jiuhai Chen; Shizhe Diao; Jiaxin Zhang 005; Yuguang Yao; Joy Rimchala; Ismini Lourentzou; Lifu Huang (CoRR, 2025)

Pisces: An Auto-regressive Foundation Model for Image Understanding and Generation. - Zhiyang Xu; Jiuhai Chen; Zhaojiang Lin; Xichen Pan; Lifu Huang; Tianyi Zhou 001; Madian Khabsa; Qifan Wang 001; Di Jin; Michihiro Yasunaga; Lili Yu; Xi Victoria Lin; et al. (CoRR, 2025)