Elamur Research⌕
☰
home / authors / Minghan Li

Minghan Li

Minghan Li has 2 papers in our library, in 2023–2024, most of them on Information retrieval & search, Vision & language; often with Jimmy Lin, Sheng-Chieh Lin, Akari Asai.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 12 · 36 works · 1,096 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 106 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5892

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

🎓Harvard UniversityCambridge · United States2024–2026 · 6 paperscurrent🎓Hong Kong Polytechnic UniversityHong Kong · China2021–2025 · 8 papers🎓University of Science and Technology of ChinaHefei · China2017–2021 · 5 papers🎓University of WaterlooWaterloo · Canada2022–2024 · 3 papers🎓Xi'an Jiaotong UniversityXi'an · China2018–2021 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Information retrieval & search · 2 worksVision & language · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval (2023 · 116 citations)
    Dense retrievers (DR) of BERT-base size have usually forced a choice: models tuned for in-domain supervised retrieval on MS MARCO tend to transfer poorly to new domains, and the reverse also holds.
  2. Unifying Multimodal Retrieval via Document Screenshot Embedding (2024 · 61 citations)
    Conventional retrieval pipelines depend on format-specific parsing such as HTML extractors and OCR. These steps are laborious and error-prone, and they discard layout and visual cues. The authors propose Document Screenshot Embedding (DSE), which skips extraction and treats a screenshot of each document as its only…

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. Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYabin Zhang et al.2022 · 254 citations
  2. How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense RetrievalFindings of the Association for Computational LinguisticsSheng-Chieh Lin, Akari Asai, Minghan Li, et al.2023 · 116 citations
  3. Unifying Multimodal Retrieval via Document Screenshot EmbeddingConference on Empirical Methods in Natural Language Processing (EMNLP)Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.2024 · 61 citations

 Co-authors here

9 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 106 times (of the 149,439 papers whose bibliographies we read); 14 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/minghan-li/