Jiuhai Chen

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 32

Top Topics

Top Venues

Publications

Dang Nguyen, Jiuhai Chen, Tianyi Zhou
Multi-Objective Linguistic Control of Large Language Models. CoRR (2024)
Ming Li, Jiuhai Chen, Lichang Chen, Tianyi Zhou
Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements. CoRR (2024)
Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Furong Huang, Cao Xiao
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. CoRR (2024)
Jiuhai Chen, Jonas Mueller
Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness. ACL (1) (2024)
Ming Li, Lichang Chen, Jiuhai Chen, Shwai He, Jiuxiang Gu, Tianyi Zhou
Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning. CoRR (2024)
Jiuhai Chen, Rifaa Qadri, Yuxin Wen, Neel Jain, John Kirchenbauer, Tianyi Zhou, Tom Goldstein
GenQA: Generating Millions of Instructions from a Handful of Prompts. CoRR (2024)
Ming Li, Lichang Chen, Jiuhai Chen, Shwai He, Jiuxiang Gu, Tianyi Zhou
Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning. ACL (Findings) (2024)
Lichang Chen, Jiuhai Chen, Chenxi Liu, John Kirchenbauer, Davit Soselia, Chen Zhu, Tom Goldstein, Tianyi Zhou, Heng Huang
OPTune: Efficient Online Preference Tuning. CoRR (2024)
Ming Li, Jiuhai Chen, Lichang Chen, Tianyi Zhou
Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements. ACL (Findings) (2024)
Ming Li, Yong Zhang, Zhitao Li, Jiuhai Chen, Lichang Chen, Ning Cheng, Jianzong Wang, Tianyi Zhou, Jing Xiao
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning. NAACL-HLT (2024)
Dang Nguyen, Jiuhai Chen, Tianyi Zhou
Multi-Objective Linguistic Control of Large Language Models. ACL (Findings) (2024)
Lichang Chen, Chen Zhu, Davit Soselia, Jiuhai Chen, Tianyi Zhou, Tom Goldstein, Heng Huang, Mohammad Shoeybi, Bryan Catanzaro
ODIN: Disentangled Reward Mitigates Hacking in RLHF. CoRR (2024)
Jiuhai Chen, Jonas Mueller
Automated Data Curation for Robust Language Model Fine-Tuning. CoRR (2024)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models. Trans. Mach. Learn. Res. 2024 (2024)
Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein
GOAT: A Global Transformer on Large-scale Graphs. ICML (2023)
Lichang Chen, Jiuhai Chen, Heng Huang, Minhao Cheng
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer. EMNLP (2023)
Jiuhai Chen, Lichang Chen, Heng Huang, Tianyi Zhou
When do you need Chain-of-Thought Prompting for ChatGPT? CoRR (2023)
Jiuhai Chen, Lichang Chen, Tianyi Zhou
It Takes One to Tango but More Make Trouble? In-Context Training with Different Number of Demonstrations. CoRR (2023)
Jiuhai Chen, Jonas Mueller
Quantifying Uncertainty in Answers from any Language Model via Intrinsic and Extrinsic Confidence Assessment. CoRR (2023)
Ming Li, Yong Zhang, Zhitao Li, Jiuhai Chen, Lichang Chen, Ning Cheng, Jianzong Wang, Tianyi Zhou, Jing Xiao
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning. CoRR (2023)
Jiuhai Chen, Lichang Chen, Chen Zhu, Tianyi Zhou
How Many Demonstrations Do You Need for In-context Learning? EMNLP (Findings) (2023)
Lichang Chen, Jiuhai Chen, Tom Goldstein, Heng Huang, Tianyi Zhou
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models. CoRR (2023)
Ming Li, Lichang Chen, Jiuhai Chen, Shwai He, Heng Huang, Jiuxiang Gu, Tianyi Zhou
Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning. CoRR (2023)
Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
Why Propagate Alone? Parallel Use of Labels and Features on Graphs. ICLR (2022)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. ICLR (2022)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features. CoRR (2022)
Jiuhai Chen, Lulu Kang, Guang Lin
Gaussian Process Assisted Active Learning of Physical Laws. Technometrics 63 (3) (2021)
Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
Why Propagate Alone? Parallel Use of Labels and Features on Graphs. CoRR (2021)
Yiwei Wang, Jiuhai Chen, Chun Liu, Lulu Kang
Particle-based energetic variational inference. Stat. Comput. 31 (3) (2021)
Jiuhai Chen, Chen Zhu, Bin Dai
Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task. CoRR (2021)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features. CoRR (2021)
Yiwei Wang, Jiuhai Chen, Lulu Kang, Chun Liu
Particle-based Energetic Variational Inference. CoRR (2020)