Eunsol Choi

4.3k total citations · 2 hit papers
48 papers, 1.9k citations indexed

About

Eunsol Choi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Eunsol Choi has authored 48 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 7 papers in Information Systems. Recurrent topics in Eunsol Choi's work include Topic Modeling (35 papers), Natural Language Processing Techniques (33 papers) and Multimodal Machine Learning Applications (13 papers). Eunsol Choi is often cited by papers focused on Topic Modeling (35 papers), Natural Language Processing Techniques (33 papers) and Multimodal Machine Learning Applications (13 papers). Eunsol Choi collaborates with scholars based in United States, Japan and Israel. Eunsol Choi's co-authors include Yejin Choi, Luke Zettlemoyer, Hannah Rashkin, Jin Yea Jang, Svitlana Volkova, Tom Kwiatkowski, Mohit Iyyer, Mark Yatskar, Wen-tau Yih and He He and has published in prestigious journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics and Proceedings of the ACM on Human-Computer Interaction.

In The Last Decade

Eunsol Choi

42 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking

2017 490 citations Hannah Rashkin, Eunsol Choi et al. profile →
QuAC: Question Answering in Context

2018 343 citations Eunsol Choi, He He et al. profile →

Peers

Eunsol Choi

AI

SPS

IS

CVPR

SP

Hannah Rashkin United States

Giovanni Da San Martino Italy

Veselin Stoyanov United States

Alberto Barrón‐Cedeño Spain

Stefan Siersdorfer Germany

Kareem Darwish Qatar

Pierpaolo Basile Italy

Steve Yuan United States

Chris Tar United States

Md Shad Akhtar India

Hannah Rashkin United States

Eunsol Choi

1.0k ×0.6

AI

475 ×1.0

SPS

322 ×0.8

IS

174 ×0.4

CVPR

70 ×0.9

SP

Citations per year, relative to Eunsol Choi Eunsol Choi (= 1×) peers Hannah Rashkin

Countries citing papers authored by Eunsol Choi

Since Specialization

Citations

This map shows the geographic impact of Eunsol Choi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eunsol Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eunsol Choi more than expected).

Fields of papers citing papers by Eunsol Choi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eunsol Choi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eunsol Choi. The network helps show where Eunsol Choi may publish in the future.

Co-authorship network of co-authors of Eunsol Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Eunsol Choi. A scholar is included among the top collaborators of Eunsol Choi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Eunsol Choi. Eunsol Choi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Harwath, David, et al.. (2025). Scaling Rich Style-Prompted Text-to-Speech Datasets. 3639–3659.

2.

Srinivasan, Anirudh, et al.. (2024). Textless Speech-to-Speech Translation With Limited Parallel Data. 16208–16224. 1 indexed citations

3.

Lee, Yoonsang, et al.. (2024). Crafting In-context Examples according to LMs’ Parametric Knowledge. 2069–2085. 1 indexed citations

4.

Xu, Fangyuan, et al.. (2024). Contrastive Learning to Improve Retrieval for Real-World Fact Checking. 264–279.

5.

Song, Yixiao, et al.. (2023). A Critical Evaluation of Evaluations for Long-form Question Answering. 3225–3245. 13 indexed citations

6.

Choi, Eunsol, et al.. (2023). Concise Answers to Complex Questions: Summarization of Long-form Answers. 9709–9728. 2 indexed citations

7.

Choi, Eunsol, et al.. (2023). Understanding Postpartum Parents' Experiences via Two Digital Platforms. Proceedings of the ACM on Human-Computer Interaction. 7(CSCW1). 1–23. 4 indexed citations

8.

Onoe, Yasumasa, et al.. (2023). Can LMs Learn New Entities from Descriptions? Challenges in Propagating Injected Knowledge. 5469–5485. 18 indexed citations

9.

Chen, Jifan, et al.. (2022). Generating Literal and Implied Subquestions to Fact-check Complex Claims. 3495–3516. 17 indexed citations

10.

Xu, Fangyuan, et al.. (2022). Modeling Exemplification in Long-form Question Answering via Retrieval. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2079–2092. 5 indexed citations

11.

Gabriel, Saadia, et al.. (2022). Misinfo Reaction Frames: Reasoning about Readers’ Reactions to News Headlines. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 3108–3127. 16 indexed citations

12.

Asai, Akari, et al.. (2022). Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resources. 3725–3743. 8 indexed citations

13.

Chen, Hung‐Ting, Michael Zhang, & Eunsol Choi. (2022). Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence. 2292–2307. 12 indexed citations

14.

Srinivasan, Anirudh & Eunsol Choi. (2022). TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages. 5723–5738. 6 indexed citations

15.

Asai, Akari, Jungo Kasai, Jonathan H. Clark, et al.. (2021). XOR QA: Cross-lingual Open-Retrieval Question Answering. 547–564. 48 indexed citations

16.

Choi, Eunsol, Omer Levy, Yejin Choi, & Luke Zettlemoyer. (2018). Ultra-Fine Entity Typing. 87–96. 111 indexed citations

17.

Choi, Eunsol, He He, Mohit Iyyer, et al.. (2018). QuAC: Question Answering in Context. 2174–2184. 343 indexed citations breakdown →

18.

Rashkin, Hannah, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, & Yejin Choi. (2017). Truth of Varying Shades: On Political Fact-Checking and Fake News. Empirical Methods in Natural Language Processing. 1 indexed citations

19.

Choi, Eunsol, Daniel Hewlett, Jakob Uszkoreit, et al.. (2017). Coarse-to-Fine Question Answering for Long Documents. 209–220. 79 indexed citations

20.

Choi, Eunsol, et al.. (2016). Extracting Structured Scholarly Information from the Machine Translation Literature. Language Resources and Evaluation. 421–425. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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