Portrait of Haoxuan Zhang

Haoxuan Zhang

Ph.D. student in Information Science (Data Science)
IDEA Lab, University of North Texas, Denton, Texas

I study how scientific knowledge is produced and evaluated in the AI era.

Research output increasingly takes the form of AI models and datasets, and large language models increasingly write the summaries and reviews that science relies on. My work addresses two questions this raises. AI documentation asks how this knowledge is recorded: I build benchmarks and methods for generating model and data cards that state what a model or dataset is, how it was built, and where it falls short. Knowledge evaluation asks how its quality is judged: I measure novelty and breakthrough innovation in science and test whether LLM-generated reviews and summaries can be trusted. The two depend on each other. Without documentation, AI work cannot be evaluated, compared, or reused; and documentation written by LLMs is itself knowledge that has to be evaluated.

I am a member of the Intelligent Data Engineering and Analytics (IDEA) Lab, advised by Prof. Haihua Chen, Prof. Ting Xiao, and Prof. Yang Zhang.

News

Latest: TopoGraphRAG-Bench accepted to NeurIPS 2026
  1. TopoGraphRAG-Bench was accepted to the NeurIPS 2026 Evaluations and Datasets Track.

  2. Two papers accepted to Findings of EMNLP 2026: MetaGAI and a survey of human–agent collaboration in scientific innovation.

  3. LongSumEval accepted to IEEE AITest 2026, and LLM-ReSum to IEEE BigDataService 2026.

  4. AdaQE-CG accepted to WWW 2026.

  5. Two papers accepted: ReviewGuard at JCDL 2025 and our study of LLM-generated peer reviews at ICDM 2025, which went on to receive the Best Poster Paper award.

  6. Started my Ph.D. at the University of North Texas.

Publications

Knowledge production and evaluation in the AI era

  1. NeurIPS 2026Knowledge evaluation

    TopoGraphRAG-Bench: Evaluating multimodal GraphRAG on layout-grounded evidence reasoning

    Li, R., Lin, J., Zhang, H., Chen, H., Ding, J., Gehringer, E., & Zhang, Y.

    In Advances in Neural Information Processing Systems (NeurIPS 2026), Evaluations and Datasets Track. OpenReview

  2. EMNLP 2026 FindingsAI documentation

    MetaGAI: A large-scale and high-quality benchmark for generative AI model and data card generation

    Zhang, H., Li, R., Zhang, Y., Liang, Z., Ding, J., Xiao, T., & Chen, H.

    In Findings of the Association for Computational Linguistics: EMNLP 2026 (pp. 34910–34931). ACL Anthology arXiv

  3. EMNLP 2026 FindingsKnowledge evaluation

    Puzzles to paradigms: A survey of human–agent collaboration in scientific innovation

    Liang, Z., Zhang, H., Chen, H., Xiao, T., Ding, J., & Zhang, Y.

    In Findings of the Association for Computational Linguistics: EMNLP 2026 (pp. 35017–35041). ACL Anthology

  4. WWW 2026AI documentation

    AdaQE-CG: Adaptive query expansion for web-scale generative AI model and data card generation

    Zhang, H., Li, R., Liang, Z., Sattari, M., Vo, P., Qu, C., Xiao, T., Ding, J., Zhang, Y., & Chen, H.

    In Proceedings of The Web Conference (WWW 2026). ACM DL

  5. AITest 2026Knowledge evaluation

    LongSumEval: Question-answering based evaluation and feedback-driven refinement for long document summarization

    Nguyen, H., Zhang, H., Zhang, Y., Ding, J., & Chen, H.

    In Proceedings of the 8th IEEE International Conference on Artificial Intelligence Testing (AITest 2026). arXiv

  6. BigDataService 2026Knowledge evaluation

    LLM-ReSum: A framework for LLM reflective summarization through self-evaluation

    Nguyen, H., Zhang, H., Zhang, Y., Chen, H., & Ding, J.

    In Proceedings of the IEEE 12th International Conference on Big Data Computing Service and Machine Learning Applications (BigDataService 2026). DOI

  7. JCDL 2025Knowledge evaluation

    ReviewGuard: Enhancing deficient peer review detection via LLM-driven data augmentation

    Zhang, H., Li, R., Xiao, T., Ding, J., & Chen, H.

    In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL 2025). arXiv

  8. ICDM 2025Best Poster PaperKnowledge evaluation

    Unveiling the merits and defects of LLMs in automatic review generation for scientific papers

    Li, R., Zhang, H., Xiao, T., Ding, J., & Chen, H.

    In Proceedings of the IEEE International Conference on Data Mining (ICDM 2025). arXiv

  9. IP&M 2025Knowledge evaluation

    IBID-CCT: A novel model for interdisciplinary breakthrough innovation detection based on the cusp catastrophe theory

    Wang, Z., Wang, N., Zhang, H., Wang, Z., Wang, Z., Ding, J., & Chen, H.

    Information Processing & Management, 62(4), 104121. DOI

  10. arXiv 2025Knowledge evaluation

    The evolving role of large language models in scientific innovation: Evaluator, collaborator, and scientist

    Zhang, H., Li, R., Zhang, Y., Xiao, T., Chen, J., Ding, J., & Chen, H.

    arXiv preprint arXiv:2507.11810. arXiv

  11. J. Informetrics 2024Knowledge evaluation

    An effective framework for measuring the novelty of scientific articles through integrated topic modeling and cloud model

    Wang, Z., Zhang, H., Chen, J., & Chen, H.

    Journal of Informetrics, 18(4), 101587. DOI

  12. JKSU-CIS 2024Knowledge evaluation

    Content-based quality evaluation of scientific papers using coarse feature and knowledge entity network

    Wang, Z., Zhang, H., Chen, H., Feng, Y., & Ding, J.

    Journal of King Saud University – Computer and Information Sciences, 36(6), 102119. DOI

  13. Electron. Libr. 2024Knowledge evaluation

    Exploring and evaluating the index for interdisciplinary breakthrough innovation detection

    Wang, Z., Qiao, X., Chen, J., Li, L., Zhang, H., Ding, J., & Chen, H.

    The Electronic Library, 42(4), 536–552. DOI

Honors and awards

ICDM 2025 Best Poster Paper and 5 more
  1. 2025

    Best Poster Paper, IEEE International Conference on Data Mining (ICDM 2025)

  2. 2025

    Graduate Student Research Award, University of North Texas

  3. 2025

    SIGIR Student Travel Grant, ACM Special Interest Group on Information Retrieval

  4. 2025

    Graduate Student Travel Grant, University of North Texas

  5. 2024.06

    Excellent Master’s Thesis, Central China Normal University

  6. 2022

    Excellent Graduate Student, Central China Normal University

Education

Ph.D., University of North Texas; M.S. and B.S., Central China Normal University
  1. 2024–present

    Ph.D. in Information Science (Data Science)

    University of North Texas, Denton, USA

  2. 2021–2024

    M.S. in Library and Information Science

    Central China Normal University, Wuhan, China

  3. 2017–2021

    B.S. in Electronic Business

    Central China Normal University, Wuhan, China

Professional service

Website Chair for 6 conferences and workshops; reviewer for 7 journals

Organizing committees

  1. 2026

    Website Chair, ACM/IEEE Joint Conference on Digital Libraries (JCDL 2026)

  2. 2025

    Website Chair, 1st International Workshop on Data Mining and AI for Law, at ICDM 2025

  3. 2025

    Website Chair, 1st Integrated Approaches to Testing Data-Centric AI Systems: Methods, Metrics, and Benchmarks (AIxSE 2025)

  4. 2024

    Website Chair, 2nd Workshop on Innovation Measurement for Scientific Communication (IMSC) in the Era of Big Data, at JCDL 2024

  5. 2024

    Website Chair, 1st Workshop on Utilizing AI/ML to Enhance Information Extraction, Organization, and Retrieval from Large-scale Archival Collections, at JCDL 2024

  6. 2023

    Website Chair, 1st Workshop on Innovation Measurement for Scientific Communication (IMSC) in the Era of Big Data, at JCDL 2023

Journal reviewing

  1. Since 2026

    Telematics and Informatics

    Information Processing & Management

    Scientometrics

  2. Since 2025

    Humanities and Social Sciences Communications

    Journal of the Association for Information Science and Technology

  3. Since 2024

    The Electronic Library

    Data Intelligence

Conference reviewing

ICDM, EMNLP, ACL, IEEE QRS, IEEE AITest, ACM/IEEE JCDL, and IEEE BigData

Teaching and mentoring

Teaching Assistant for DTSC 5502 since 2024
  1. 2024.08–present

    Teaching Assistant, DTSC 5502 (Section 401): Principles and Techniques for Data Science

    University of North Texas. Fall 2024, Spring 2025, Fall 2025, Spring 2026.

  2. 2025.05–2025.07

    Research Assistant, UNT AI/CS Summer Research Program

    University of North Texas