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Nan Ding

Nan Ding has 2 papers in our library, in 2018–2025, most of them on Vision & language; often with Fei Sha, Jin Peng Zhou, Kilian Q. Weinberger.

2 papers in our library · 2018–2025

OpenAlex · ORCID · h-index 15 · 29 works · 3,173 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 594 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #1305

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

🏢GoogleMountain View · United States2014–2023 · 16 paperscurrent🎓The University of Texas at AustinAustin · United States2018 · 2 papers🎓Tsinghua UniversityBeijing · China2010 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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).Computer Science · 2 worksComputer Vision and Pattern Recognition · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 1Research subjects and languages the work is about.Vision & language · 1 work

 Works by year

2020s

20251 paper

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning (2018 · 2,348 citations)
    The paper addresses the shortage of large and varied training data for automatic image captioning. Earlier resources such as MS-COCO are curated but small for deep models. The authors introduce Conceptual Captions, a set of about 3.3M image–description pairs harvested from the Alt-text attribute of web images. They…
  2. Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations (2025 · 3 citations)
    Using a language model to grade other models is cheap, but it breaks down on frontier tasks such as Olympiad math or graduate-level physics.

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. Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image CaptioningAnnual Meeting of the Association for Computational Linguistics (ACL)Piyush Sharma, Nan Ding, Sebastian Goodman, et al.2018 · 2,348 citations
  2. Do Transformer Modifications Transfer Across Implementations and Applications? ↗Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yetSharan Narang et al.2021 · 123 citations
  3. Graders Should Cheat: Privileged Information Enables Expert-Level Automated EvaluationsConference on Empirical Methods in Natural Language Processing (EMNLP)Jin Peng Zhou, Séb Arnold, Nan Ding, et al.2025 · 3 citations

 Co-authors here

7 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 594 times (of the 149,439 papers whose bibliographies we read); 95 citing papers with a page here →.

Updated

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