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Mingqi Gao

Mingqi Gao has 3 papers in our library, in 2023–2026, most of them on Evaluation & benchmarks, Summarization, Text generation; often with Xiaojun Wan, Jie Ruan, Xinyu Hu.

3 papers in our library · 2023–2026

OpenAlex · ORCID · h-index 14 · 68 works · 817 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 151 times in our library · ⭐ Paper Stars ranking: #5711

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

🎓Peking UniversityBeijing · China2022–2026 · 17 paperscurrent🎓Southern University of Science and TechnologyShenzhen · China2022–2026 · 11 paperscurrent🎓University of SheffieldSheffield · United Kingdom2025–2026 · 4 papersEmployment since 2025 · Research Associate, School of Computer Sciencecurrent🎓Chongqing UniversityChongqing · China2014–2019 · 14 papersEducation 2014–2017 · College of Computer Science🎓University of WarwickCoventry · United Kingdom2019–2024 · 8 papersEducation 2019–2024 · Warwick Manufacturing Group

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 4Research subjects and languages the work is about.Evaluation & benchmarks · 2 worksText generation · 1 workSummarization · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. LLM-based NLG Evaluation: Current Status and Challenges (2025 · 153 citations)
    Judging natural language generation is difficult because a good output has no single correct form and must satisfy several quality criteria at once.
  2. Human-like Summarization Evaluation with ChatGPT (2023 · 128 citations)
    Automatic metrics for text summarization, such as ROUGE and embedding-based scores, often disagree with human judgment and offer little interpretability.
  3. Minos: A Multimodal Evaluation Model for Bidirectional Generation Between Image and Text (2026)
    Automatic judging of multimodal outputs is still unreliable. Classic metrics often disagree with human ratings, need references, or only work for one task. Existing MLLM-based judges such as LLaVA-Critic and UnifiedReward train on large but loosely filtered data and do not handle both image-to-text (I2T) and…

 Co-authors here

11 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 151 times (of the 149,439 papers whose bibliographies we read); 34 citing papers with a page here →.

Updated

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