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Furong Huang

Furong Huang has 2 papers in our library, in 2023–2026, most of them on Language models & pretraining, Vision & language; often with Dinesh Manocha, Fuxiao Liu, Lichang Chen.

2 papers in our library · 2023–2026

OpenAlex · ORCID · h-index 18 · 123 works · 1,319 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 176 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4728

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of Maryland, College ParkCollege Park · United States2014–2026 · 60 paperscurrent🎓Jinan UniversityGuangzhou · China2021–2026 · 6 paperscurrent🎓University of California, IrvineIrvine · United States2011–2016 · 8 papers🎓Harbin Institute of TechnologyHarbin · China2006–2025 · 6 papers🏢Capital OneTysons Corner · United States2024–2025 · 4 papers🎓Irvine UniversityCerritos · United States2013–2016 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models (2023 · 335 citations)
    Large vision-language models (LVLMs) often let language priors override what an image actually shows, and their vision side can misread pictures with high confidence.
  2. Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward Modeling (2026)
    Reward models (RMs) trained on human preference pairs often fail under distribution shift or small targeted edits.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
  2. MLSys: The New Frontier of Machine Learning Systems ↗arXiv (Cornell University) · no summary yetAlexander Ratner et al.2019 · 19 citations
  3. Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Pankayaraj Pathmanathan, Furong Huang2026

 Co-authors here

6 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 176 times (of the 149,439 papers whose bibliographies we read); 52 citing papers with a page here →.

Updated

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