Jin Yong Yoo

719 total citations · 1 hit paper
6 papers, 364 citations indexed

About

Jin Yong Yoo is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Jin Yong Yoo has authored 6 papers receiving a total of 364 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Information Systems and 2 papers in Signal Processing. Recurrent topics in Jin Yong Yoo's work include Topic Modeling (5 papers), Adversarial Robustness in Machine Learning (3 papers) and Natural Language Processing Techniques (3 papers). Jin Yong Yoo is often cited by papers focused on Topic Modeling (5 papers), Adversarial Robustness in Machine Learning (3 papers) and Natural Language Processing Techniques (3 papers). Jin Yong Yoo collaborates with scholars based in United States and South Korea. Jin Yong Yoo's co-authors include Yanjun Qi, John X. Morris, Eli Lifland, Di Jin, Jake Grigsby, Beomsu Kim, Seokjun Seo, Sang‐Bum Kim, Buru Chang and Seungju Han and has published in prestigious journals such as Mobile Information Systems, arXiv (Cornell University) and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

In The Last Decade

Jin Yong Yoo

6 papers receiving 347 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.

TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP

2020 302 citations John X. Morris, Eli Lifland et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jin Yong Yoo United States	5	324	82	47	40	34	6	364
John X. Morris United States	5	342 1.1×	86 1.0×	48 1.0×	46 1.1×	33 1.0×	11	394
Eli Lifland United States	4	326 1.0×	83 1.0×	48 1.0×	38 0.9×	31 0.9×	4	374
Jake Grigsby United States	2	268 0.8×	66 0.8×	37 0.8×	33 0.8×	26 0.8×	2	313
Shuhuai Ren China	8	404 1.2×	106 1.3×	52 1.1×	99 2.5×	34 1.0×	14	477
Yihe Deng China	2	390 1.2×	115 1.4×	47 1.0×	42 1.1×	32 0.9×	4	409
Ahoud Alhazmi Australia	4	248 0.8×	68 0.8×	48 1.0×	42 1.1×	21 0.6×	8	293
Roman Englert Germany	8	176 0.5×	107 1.3×	38 0.8×	46 1.1×	19 0.6×	23	262
Hongzhao Huang United States	10	279 0.9×	91 1.1×	40 0.9×	27 0.7×	12 0.4×	17	344
Jiazhu Dai China	7	267 0.8×	86 1.0×	62 1.3×	20 0.5×	22 0.6×	17	304
Daniel Beck Australia	8	304 0.9×	21 0.3×	45 1.0×	62 1.6×	7 0.2×	29	365

Countries citing papers authored by Jin Yong Yoo

Since Specialization

Citations

This map shows the geographic impact of Jin Yong Yoo'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 Jin Yong Yoo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Yong Yoo more than expected).

Fields of papers citing papers by Jin Yong Yoo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin Yong Yoo. 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 Jin Yong Yoo. The network helps show where Jin Yong Yoo may publish in the future.

Co-authorship network of co-authors of Jin Yong Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Yong Yoo. A scholar is included among the top collaborators of Jin Yong Yoo 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 Jin Yong Yoo. Jin Yong Yoo 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:

6 of 6 papers shown

1.

Han, Seungju, Beomsu Kim, Jin Yong Yoo, et al.. (2022). Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 5114–5132. 9 indexed citations

2.

Morris, John X., Jin Yong Yoo, & Yanjun Qi. (2020). TextAttack: Lessons learned in designing Python frameworks for NLP. 126–131. 4 indexed citations

3.

Morris, John X., Eli Lifland, Jin Yong Yoo, et al.. (2020). TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP. 119–126. 302 indexed citations breakdown →

4.

Morris, John X., Eli Lifland, Jin Yong Yoo, & Yanjun Qi. (2020). TextAttack: A Framework for Adversarial Attacks in Natural Language Processing. arXiv (Cornell University). 24 indexed citations

5.

Yoo, Jin Yong, John X. Morris, Eli Lifland, & Yanjun Qi. (2020). Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples. 323–332. 24 indexed citations

6.

Lee, Mun‐Kyu, et al.. (2017). Analysis and Improvement on a Unimodal Haptic PIN-Entry Method. Mobile Information Systems. 2017. 1–17. 1 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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