---
title: "Jinhyuk Lee — author profile and papers"
description: "Jinhyuk Lee, Johns Hopkins University: 3 papers on Elamur Research (2019–2021), h-index 27 — affiliations, topics, co-authors and who cites them in our…"
canonical: "https://research.elamur.ai/free/en/authors/jinhyuk-lee/"
---
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# Jinhyuk Lee

3 papers on this site · 2019–2021

current affiliation [Johns Hopkins University](https://ror.org/00za53h95), Baltimore, United States; [Sejong University](https://ror.org/00aft1q37), Seoul, South Korea; [Korea Expressway Corporation (South Korea)](https://ror.org/027286m03), Gimcheon-si, South Korea

Jinhyuk Lee has 3 papers on this site, in 2019–2021, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Question answering](https://md.research.elamur.ai/free/en/topics/question-answering/), [Information retrieval & search](https://md.research.elamur.ai/free/en/topics/information-retrieval/); often with [Ali Farhadi](https://md.research.elamur.ai/free/en/authors/ali-farhadi/), [Ankur Parikh](https://md.research.elamur.ai/free/en/authors/ankur-parikh/), [Danqi Chen](https://md.research.elamur.ai/free/en/authors/danqi-chen/).

[OpenAlex](https://openalex.org/A5002413587) · [ORCID](https://orcid.org/0000-0003-4972-239X) · [**h-index 27**](https://openalex.org/authors/A5002413587) · [72 works](https://openalex.org/works?filter=author.id:A5002413587) · [9 801 citations](https://openalex.org/works?filter=author.id:A5002413587&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[3 works on this site](https://md.research.elamur.ai/free/en/authors/jinhyuk-lee/#papers) · [3 737 citations in our library](https://md.research.elamur.ai/free/en/authors/jinhyuk-lee/cited-by/) · 6 more works in our library

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

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Jinhyuk+Lee) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Jinhyuk+Lee) · [dblp](https://dblp.org/search?q=Jinhyuk+Lee) · [ACL Anthology](https://aclanthology.org/search/?q=Jinhyuk+Lee)

## Affiliations

- [Sejong University](https://ror.org/00aft1q37) · Seoul, South Korea —current · 2025 on 2 papers
- [Johns Hopkins University](https://ror.org/00za53h95) · Baltimore, United States —current · 2025 on 1 paper
- [Korea Expressway Corporation (South Korea)](https://ror.org/027286m03) · Gimcheon-si, South Korea —current · 2025 on 1 paper
- [Korea University](https://ror.org/047dqcg40) · Seoul, South Korea —2016–2024 on 26 papers
- [Princeton University](https://ror.org/00hx57361) · Princeton, United States —2020–2023 on 6 papers
- [Google (United States)](https://ror.org/00njsd438) · Mountain View, United States —2022–2023 on 3 papers
- [Korea Research Institute of Bioscience and Biotechnology](https://ror.org/03ep23f07) · Daejeon, South Korea —2013–2022 on 3 papers
- [Korea University of Science and Technology](https://ror.org/000qzf213) · Daejeon, South Korea —2013–2022 on 3 papers
- [Korea University](https://ror.org/05m1gnk07) · Tokyo, Japan —2018–2021 on 2 papers
- [University of Washington](https://ror.org/00cvxb145) · Seattle, United States —2019–2020 on 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 13 more institutions on single bylines are not listed.

## Topics

[Language models & pretraining 1](https://md.research.elamur.ai/free/en/topics/language-models/) · [Question answering 1](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Information retrieval & search 1](https://md.research.elamur.ai/free/en/topics/information-retrieval/)

## Papers

The most cited first (OpenAlex and our library).

1. **[BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://md.research.elamur.ai/free/en/papers/lee-2019-biobert-pre-trained-biomedical-language/)** *(2019 · 8 281 citations)* Biomedical literature grows faster than researchers can read it, so automatic text mining matters more each year.
2. **[Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index](https://md.research.elamur.ai/free/en/papers/seo-2019-real-time-open-domain-question/)** *(2019 · 216 citations)* Standard open-domain QA systems such as DrQA first retrieve a handful of documents and then run a neural reader over them for each new question.
3. **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/)** *(2021 · 168 citations)* Dense retrievers such as DPR are often seen as having replaced sparse methods like BM25 in open-domain QA.

## Also in our library

6 more works of theirs are in our library without a page here yet; they will appear as we publish them.

## Co-authors here

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

- [Ali Farhadi](https://md.research.elamur.ai/free/en/authors/ali-farhadi/)
- [Ankur Parikh](https://md.research.elamur.ai/free/en/authors/ankur-parikh/)
- [Danqi Chen](https://md.research.elamur.ai/free/en/authors/danqi-chen/)
- [Hannaneh Hajishirzi](https://md.research.elamur.ai/free/en/authors/hannaneh-hajishirzi/)
- [Minjoon Seo](https://md.research.elamur.ai/free/en/authors/minjoon-seo/)
- [Sungdong Kim](https://md.research.elamur.ai/free/en/authors/sungdong-kim/)
- [Tom Kwiatkowski](https://md.research.elamur.ai/free/en/authors/tom-kwiatkowski/)
- [Wonjin Yoon](https://md.research.elamur.ai/free/en/authors/wonjin-yoon/)
- [Zexuan Zhong](https://md.research.elamur.ai/free/en/authors/zexuan-zhong/)

## Cited by

Papers of our library cite their works 3 737 times (of the 140 884 papers whose bibliographies we read); [208 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jinhyuk-lee/cited-by/).
