Yue Huang | 黄跃

PhD Student of Computer and Science · University of Notre Dame

About Me

I’m a second-year PhD student in MINE Lab of Computer Science and Engineering (CSE) at the University of Notre Dame began from Fall 2024, supervised by Leonard C. Bettex Collegiate Prof. Xiangliang Zhang. I’m also a graduate student in Foundation Models and Applications Lab (FMAL) at Lucy Family Institute for Data & Society. I obtained my bachelor’s degree from Sichuan University in 2024. In 2025 summer, I worked with Prasanna Sattigeri and Pin-Yu Chen at MIT-IBM Watson AI Lab and IBM Research AI. Previously, I was a visiting student under the guidance of Prof. Lichao Sun. This experience was enhanced by mentorship from Prof. Philip S. Yu. Earlier before, I worked under Prof. Tang Jie and Dr. Xiao Liu at Tsinghua University.

I welcome the opportunity to connect with colleagues in my field as well as those from interdisciplinary areas.
My recent research centers on: (1) the science of foundation models, with a particular emphasis on their trustworthiness; (2) edge or tailed alignment of foundation models; and (3) dynamic evaluation protocols tailored for generative models.
If you are interested in my research, please contact me via email or for an in-person conversation.

Research Interests

My research is centered on three pivotal questions:

Trustworthy, Aligned, and Democratically Governed Generative Foundation Models. This line of inquiry seeks to develop robust frameworks for evaluating trustworthiness and to identify strategies for enhancing the trustworthiness of these models within specific application domains. This includes: ICML'24, NAACL'24, ACM CCS'24, WWW'24, EMNLP'24, NeurIPS'24, ICLR'25d, and NeurIPS'25a.

Data-Driven Scalable Alignment for General-Purpose AI Systems. This research emphasizes data-centric methods to enable scalable model alignment and evolution, ensuring that they adhere to human values and ethical paradigms throughout the development process. This includes: ACL'24, EMNLP'24, ICLR'25a, ICLR'25b, AAAI'26a, and AAAI'26b.

Scientific AI and Societal AI. This research area critically assesses the practical impact of generative models, with a particular focus on their application and AI4Science, exploring its transformative potential and interdisciplinary contributions in fields such as agentic models, social sciences, and beyond. This includes: ICLR'24, ICLR'25c, and NeurIPS'25b.

News

Check out latest preprints: General Agentic Guardrail, Computing of Foundation Model Research, Trustworthiness of Generative Foundation Models

Nov. 2025 I was selected as Jetstream2 NAIRR AI Fellow. Four papers are accepted by AAAI 2026 (Priority Alignment (SPA) and SECURE are selected as oral, RefineLab and RMO are selected as poster). Yujun's LabSafetyBench is accepted by Nature Machine Intelligence, congrats!

Oct. 2025 I will present a tutorial of "Science of Trustworthy Generative Foundation Models" in NeurIPS 2025, and we are organizing one workshop at NeurIPS 2025. Hope to see you in Mexico City!

Sep. 2025 We have four papers accepted by NeurIPS 2025 (huge thanks to Xiangqi, Yanbo, and all other co-authors), and another paper (EmoNest) is accepted by NeurIPS 2025 Creative AI track (Try our demo in Dec. at conference). See you in San Diego for our posters!

Aug. 2025 One paper is accepted by EMNLP 2025 Findings and two paper are accepted by CIKM 2025.

July. 2025 Preference Leakage won the best paper award of DIG-BUGs@ICML 2025, PsychometricBench won the best paper award of SciSocLLM@KDD'25. One paper accepted by COLM 2025.

May. 2025 Two papers are accepted by ACL 2025 (1 Main + 1 Findings).

Mar. 2025 TrustEval is accepted by NAACL 2025 Demo and UPME is accepted by CVPR 2025.

Jan. 2025 Four papers have been accepted by ICLR 2025! I was selected as KAUST Rising Stars in AI Symposium 2025 (24/300+).

Dec. 2024 I will join IBM Research as a Research Scientist Intern in 2025 Summer. See you in Cambridge, MA.

Sep. 2024 HonestLLM has been accepted by NeurIPS 2024. Congratulations to Chujie! Another paper has been accepted by main conference of EMNLP 2024.

Aug. 2024 Attack LLM-as-a-Judge has been accepted by ACM CCS 2024. OpenAI's Researcher Access Program is Awarded.

May. 2024 TrustLLM has been accepted by ICML 2024. Another paper has been accepted by main conference of ACL 2024.

Mar. 2024 One paper has been accepted by NAACL 2024. Another paper has been accepted as a short paper of WWW 2024.

Jan. 2024 MetaTool has been accepted by ICLR 2024!

Incoming Event

Incoming Workshop at NeurIPS'25:

NeurIPS 2025 Workshop on Socially Responsible and Trustworthy Foundation Models (ResponsibleFM) - Call for Papers

Incoming Tutorials at NeurIPS'25 and AAAI'26:

      NeurIPS 2025 Workshop

      December 2025 | Mexico City, Mexico

      AAAI 2026

      January 20-27, 2026 | Singapore

Selected Publications

Disclaimer: This material is presented to ensure the timely dissemination of scholarly works. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms invoked by each author’s copyright.

*: Equal Contribution

SPA: Achieving Consensus in LLM Alignment via Self-Priority Optimization

Yue Huang, Xiangqi Wang, Xiangliang Zhang

The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026 Oral)

RMO: Towards Better LLM Alignment via Reshaping Reward Margin Distributions

Yanchi Ru*, Yue Huang*, Xiangliang Zhang

The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026)

Better Datasets Start From RefineLab: Automatic Optimization for High-Quality Dataset Refinement

Xiaonan Luo*, Yue Huang*, Ping He, Xiangliang Zhang

The 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026)

ChemOrch: Empowering LLMs with Chemical Intelligence via Groundbreaking Synthetic Instructions

Yue Huang*, Zhengzhe Jiang*, Xiaonan Luo, Kehan Guo, Haomin Zhuang, Yujun Zhou, Zhengqing Yuan, Xiaoqi Sun, Jules Schleinitz, Yanbo Wang, Shuhao Zhang, Mihir Surve, Nitesh V Chawla, Olaf Wiest, Xiangliang Zhang

The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)

[Code]

AdaReasoner: Adaptive Reasoning Enables More Flexible Thinking

Xiangqi Wang*, Yue Huang*, Yanbo Wang, Xiaonan Luo, Kehan Guo, Yujun Zhou, Xiangliang Zhang

The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025 Spotlight)

[Code]

Exposing and Patching the Flaws of Large Language Models in Social Character Simulation

Yue Huang*, Zhengqing Yuan*, Yujun Zhou, Kehan Guo, Xiangqi Wang, Haomin Zhuang, Weixiang Sun, Lichao Sun, Jindong Wang, Yanfang Ye, Xiangliang Zhang

Second Conference on Language Modeling (COLM 2025)

[Dataset]

DataGen: Unified Synthetic Dataset Generation via Large Language Models

Yue Huang*, Siyuan Wu*, Chujie Gao, Dongping Chen, Qihui Zhang, Yao Wan, Tianyi Zhou, Chaowei Xiao, Jianfeng Gao, et al.

The Thirteenth International Conference on Learning Representations (ICLR 2025)

[Toolkit] [Website] [Tutorial Video]

Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge

Jiayi Ye*, Yanbo Wang*, Yue Huang*, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V Chawla, Xiangliang Zhang

The Thirteenth International Conference on Learning Representations (ICLR 2025)

[Website]

GUI-World: A GUI-oriented Dataset for Multimodal LLM-based Agents

Dongping Chen*, Yue Huang*, Siyuan Wu, Jingyu Tang, Huichi Zhou, Qihui Zhang, Zhigang He, et al.

The Thirteenth International Conference on Learning Representations (ICLR 2025)

[Website] [Dataset] [Model]

TrustLLM: Trustworthiness in Large Language Models

Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, et al.

2024 International Conference on Machine Learning (ICML 2024)

(Highlighted by United States Department of Homeland Security (DHS) & International AI Safety Report, Invited Talk at IBM Research)

[Code&Toolkit] [Website] [Dataset] [Docs.]

MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use

Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, et al.

The Twelfth International Conference on Learning Representations (ICLR 2024)

[Code]

1+1>2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?

Yue Huang*, Chenrui Fan*, Yuan Li, Siyuan Wu, et al.

The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)

HonestLLM: Toward an Honest and Helpful Large Language Model

Chujie Gao*, Siyuan Wu*, Yue Huang*, Dongping Chen*, Qihui Zhang*, et al.

Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)

[Code]

Talks & Guest Lecture

Nov. 2025 Conference Tutorial: Responsible Generative Foundation Models: From Principles to Real-World Impact @ ICDM 2025

Nov. 2025 Conference Tutorial: Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era @ CIKM 2025

Nov. 2025 Conference Tutorial: Socially Responsible and Trustworthy Generative Foundation Models: Principles, Challenges, and Practices @ CIKM 2025

May. 2025 Toward Socially Impactful and Trustworthy Generative Foundation Models @ University of Illinois Urbana-Champaign (Host: Heng Ji & Chi Han)

Apr. 2025 On the Trustworthiness of Generative Foundation Models @ KAUST Rising Stars in AI Symposium 2025

Mar. 2025 Guest Lecture: Trustworthiness in Large Language Models @ University of Virginia (Instructor: Chirag Agarwal)

Feb. 2025 Guest Lecture: Toward Socially Impactful and Trustworthy Generative Foundation Models @ University of Southern California (Instructor: Jieyu Zhao)

Jul. 2024 Bias of Large Language Models @ Technical University of Munich

Feb. 2024 Trustworthiness in Large Language Models @ IBM Research

Honors and Awards

Nov. 2025 Jetstream2 NAIRR AI Fellow

Aug. 2025 NSF Discover ACCESS Project

Aug. 2025 NSF POSE Training Award (Role: Industry Mentor)

Jul. 2025 Best Paper Award of SciSocLLM@KDD’25

Jul. 2025 Best Paper Award of DIG-BUG@ICML’25

Jan. 2025 KAUST AI Rising Star

Jul. 2024 OpenAI's Researcher Access Program

Jun. 2024 Elite Student of School of Cyber Science and Engineering, Sichuan University (网安菁英)

Jan. 2024 Microsoft Accelerate Foundation Models Research

Academic Participation

Journal Reviewer: Nature Communication, IEEE Transactions on Artificial Intelligence (TAI), IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), ACM Transactions on Intelligent Systems and Technology (ACM TIST)
Conference Reviewer: NeurIPS (2025-), ICLR (2024-), ICML (2025-), AAAI (2025-), KDD (2025-), ICDM (2024-), WWW (2024-), COLM (2025-), ACL Rolling Review (2024-), EMNLP Demo Track (2024-), NAACL Demo Track (2025-), ACL Demo Track (2025-)
Technical Committee Member of 2024 IEEE Computer Society North America Student Challenge

Educations

Sep. 2024
Present

Ph.D in Computer Science and Engineering

University of Notre Dame

Sep. 2020
Jun. 2024

BEng. in Cybersecurity

Sichuan University

Internships

May. 2025
Aug. 2025

Research Intern

IBM Research

Sep. 2023
Jan. 2024

Research Intern

Tsinghua University KEG

Acknowledgment

I am honored that my research is funded, supported, or recognized by:

Misc

I spent 18 years in my hometown, Fujian 🇨🇳, and had 4 wonderful years of university life in Sichuan 🌶️ (I can handle spicy food!).
I love exchanging ideas with people from different fields 🌍—it helps me see the world more broadly.
My favorite singers are Eason Chan and Steve Chou;小剛 🎤. Lately, I’ve been listening to Patti Tsai.
My favorite sports are swimming 🏊 and badminton 🏸. I also enjoy capturing scenic moments with my camera 📷.
I’m deeply grateful to those who’ve helped me along the way 🙏—thank you for helping me go further!