---
title: "South Korea — research institutions, scientists and papers"
description: "South Korea: 12 institutions with papers in our library in 2 agglomerations, 35 people with a page, 44 works, 78,212 citations."
canonical: "https://research.elamur.ai/free/en/countries/south-korea/"
---
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# South Korea

Country 12 institutions in 2 agglomerations · [all countries](https://md.research.elamur.ai/free/en/countries/)

[**12** institutions with a page](https://md.research.elamur.ai/free/en/countries/south-korea/#institutions) · [**2** agglomerations](https://md.research.elamur.ai/free/en/countries/south-korea/#agglomerations) · [**35** people with a page](https://md.research.elamur.ai/free/en/countries/south-korea/#authors) · [**44** works in our library](https://md.research.elamur.ai/free/en/countries/south-korea/#works) · [**78,212** citations of their works](https://md.research.elamur.ai/free/en/countries/south-korea/#works)

## About

### Profile

South Korea appears in the library's directory of [research organisations](https://md.research.elamur.ai/free/en/orgs/) through its own [country listing](https://md.research.elamur.ai/free/en/orgs/country/kr/). That listing gathers the universities, laboratories, companies and other bodies based in the country whose researchers wrote more than one of the papers in our library. The entries are ordered by the cited work their scientists did while working at each place. The listing shows where Korean research appears in this collection. It is not a survey of science in South Korea as a whole.

The organisations fall into two broad groups: universities and corporate research units, most of them belonging to large technology firms. Nearly all are in the capital region, centred on Seoul and the nearby city of Seongnam-si. The exception is a university in Daejeon. Academic and industrial work sit side by side in this listing, and a small group of organisations accounts for most of the cited output found here.

At the country level the directory shows organisations rather than individual scientists, specific papers or research topics. Those details sit on the pages of the separate institutions, which can be reached through the links below. What follows describes the organisations themselves: what kind each is, where it is based, and how its share of works and citations on this site compares with the others.

### The institutions and their order

[Korea University](https://md.research.elamur.ai/free/en/universities/korea-university/) in Seoul heads the list. Its set of works on the site is small but heavily cited, so its position rests on a few papers that are widely referred to.

[Seoul National University](https://md.research.elamur.ai/free/en/universities/seoul-national-university/), also in Seoul, comes next. It has the largest body of work of any Korean organisation here and by far the largest citation total. If the list counted citations alone, it would come first among Korean institutions on this site. Its place just behind Korea University shows that the ordering measures the cited work scientists did at an institution, which differs from adding up every citation linked to its papers.

Two corporate entries follow: [Naver](https://md.research.elamur.ai/free/en/companies/naver/) and [NAVER Cloud](https://md.research.elamur.ai/free/en/companies/naver-cloud/). Both are listed in Seongnam-si. Each has a moderate body of well-cited work, and each has a citation total larger than Korea University's. They share a name and a city, but the directory keeps them as separate entries, each with its own page.

[Korea Advanced Institute of Science and Technology](https://md.research.elamur.ai/free/en/universities/korea-advanced-institute-of-science-and-technology/) in Daejeon is the only organisation on the list outside the Seoul area. Among Korean institutions here, only Seoul National University has more works. Its citation total, however, is well below those of the organisations ranked above it. Its contribution is spread across many papers rather than resting on a few highly cited ones.

The [University of Seoul](https://md.research.elamur.ai/free/en/universities/university-of-seoul/) comes next, with a small number of works and a modest citation total. [Yonsei University](https://md.research.elamur.ai/free/en/universities/yonsei-university/), another Seoul institution, follows. It has more works than several of its neighbours on the list, and its citations fall in the middle range.

[LG AI Research](https://md.research.elamur.ai/free/en/companies/lg-ai-research/), a corporate laboratory in Seoul, comes after Yonsei. It has a handful of works and a citation total close to Yonsei's. [Samsung (South Korea)](https://md.research.elamur.ai/free/en/companies/samsung-south-korea/), also listed in Seoul, has very few works on the site. Those works are cited more than the output of several universities placed near it, so their reach is larger than their number would suggest.

Three more Seoul universities complete the list. [Hanyang University](https://md.research.elamur.ai/free/en/universities/hanyang-university/) and [Kyung Hee University](https://md.research.elamur.ai/free/en/universities/kyung-hee-university/) each have a small presence here and have drawn few citations so far. [Konkuk University](https://md.research.elamur.ai/free/en/universities/konkuk-university/) is listed last, even though its citation total is higher than those of several institutions above it. The order clearly does not follow total citations alone.

### Universities

Most of the Korean organisations on this site are universities. Among the works here, the largest academic presence is at Seoul National University, which leads all Korean institutions in both works and citations. Korea University has a narrower set of papers that are widely cited. The Korea Advanced Institute of Science and Technology contributes a broad set of works with more limited citation.

The other university entries are smaller. Yonsei University has a mid-sized group of papers. The University of Seoul, Hanyang University, Kyung Hee University and Konkuk University each appear with only a few works, enough to meet the directory's threshold. Some of these smaller entries already show solid citation, such as Konkuk University. Others, such as Kyung Hee University, have drawn little so far.

Seoul dominates the academic picture. Every listed university except the one in Daejeon is in the capital. On this site, Korean university research is concentrated in one metropolitan area, with a single substantial centre elsewhere in the country.

### Companies

Industrial entries form a notable part of the Korean presence here. The corporate names on the list are Naver, NAVER Cloud, LG AI Research and Samsung (South Korea). Naver and NAVER Cloud rank above every university except Korea University and Seoul National University. Taken together, their citation totals are among the largest of any Korean organisations on the site.

The name of LG AI Research marks it as a laboratory devoted to artificial intelligence. The country listing does not give the topics of its papers, so its subjects are found on its own page. Samsung (South Korea) appears with few works but notable citation. In this collection, a small number of papers from a large firm can carry real weight.

The country listing does not show shared authorship or overlap in topics between companies and universities. Whether Korean corporate laboratories and universities publish together can be checked on the individual institution pages, which give the works and co-authors behind each entry.

### Geography

The geographic spread is narrow. Seoul is home to most of the listed universities and to LG AI Research and Samsung (South Korea). Seongnam-si, in the wider capital area, is home to both Naver entries. Daejeon appears only as the home of the Korea Advanced Institute of Science and Technology.

On this site, then, Korean research activity is concentrated in and around the capital, with one further centre to the south. This pattern reflects only the institutions whose researchers have written papers held here. Other Korean research centres may exist without yet meeting the directory's threshold.

### Reading the list

Three points help in reading the country listing. First, inclusion depends on the papers held in this library. An organisation enters the list once its researchers have written more than one work here, so the list will change as the collection grows. Second, the order reflects the cited work scientists did at each institution, not raw totals. That is why Korea University leads despite a smaller citation sum than Seoul National University, and why Konkuk University sits last despite being cited more than some entries above it. Third, the size of an entry's body of work and its citation total often diverge. Samsung (South Korea) and Korea University have few works with heavy citation. The Korea Advanced Institute of Science and Technology has many works with lighter citation.

At the country level the directory does not show individual scientists, landmark papers, research topics, collaborations or trends across years. Each of these is on the page of the relevant institution, which lists its people in order, its works with citations, and the topics and units it covers. The general directory of organisations of all kinds is the place to compare South Korea's entries with those of other countries.

## Where

## Agglomerations (2)

1. [**Seoul**11 institutions*76,422 citations*](https://md.research.elamur.ai/free/en/agglomerations/seoul/)
2. [**Daejeon**1 institution*1,790 citations*](https://md.research.elamur.ai/free/en/agglomerations/daejeon/)

## Institutions (12)

### 🎓 Universities (8)

**[Seoul National University](https://md.research.elamur.ai/free/en/universities/seoul-national-university/)**University · [Seoul](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*14 works · 44,563 citations*

**[Korea University](https://md.research.elamur.ai/free/en/universities/korea-university/)**University · [Seoul](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*4 works · 8,679 citations*

**[Korea Advanced Institute of Science and Technology](https://md.research.elamur.ai/free/en/universities/korea-advanced-institute-of-science-and-technology/)**University · [Daejeon](https://md.research.elamur.ai/free/en/agglomerations/daejeon/), South Korea*9 works · 1,790 citations*

**[Yonsei University](https://md.research.elamur.ai/free/en/universities/yonsei-university/)**University · [Seoul](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*6 works · 446 citations*

**[Konkuk University](https://md.research.elamur.ai/free/en/universities/konkuk-university/)**University · [Seoul](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*3 works · 369 citations*

### 🏢 Companies (4)

**[Naver](https://md.research.elamur.ai/free/en/companies/naver/)**Company · [Seongnam-si](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*7 works · 10,725 citations*

**[NAVER Cloud](https://md.research.elamur.ai/free/en/companies/naver-cloud/)**Company · [Seongnam-si](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*6 works · 9,944 citations*

**[Samsung](https://md.research.elamur.ai/free/en/companies/samsung-south-korea/)**Company · [Seoul](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*2 works · 1,050 citations*

**[LG AI Research](https://md.research.elamur.ai/free/en/companies/lg-ai-research/)**Company · [Seoul](https://md.research.elamur.ai/free/en/agglomerations/seoul/), South Korea*3 works · 350 citations*

[See all 12 institutions →](https://md.research.elamur.ai/free/en/countries/south-korea/institutions/)

## People (35)

Authors with a page confirmed at its institutions, the most cited first.

[🧑‍🔬**Jinhyuk Lee** Korea University 3 papers here · 13,042 citations](https://md.research.elamur.ai/free/en/authors/jinhyuk-lee/) · [🧑‍🔬**Kenton Lee** Korea University 13 papers here · 11,852 citations](https://md.research.elamur.ai/free/en/authors/kenton-lee/) · [🧑‍🔬**Sungdong Kim** Naver 3 papers here · 9,261 citations](https://md.research.elamur.ai/free/en/authors/sungdong-kim/) · [🧑‍🔬**Wonjin Yoon** Korea University 2 papers here · 8,281 citations](https://md.research.elamur.ai/free/en/authors/wonjin-yoon/) · [🧑‍🔬**Minjoon Seo** Korea Advanced Institute of Science and Technology 8 papers here · 4,610 citations](https://md.research.elamur.ai/free/en/authors/minjoon-seo/) · [🧑‍🔬**Liwei Jiang** Seoul National University 9 papers here · 2,107 citations](https://md.research.elamur.ai/free/en/authors/liwei-jiang/) · [🧑‍🔬**Jamin Shin** Naver 4 papers here · 1,512 citations](https://md.research.elamur.ai/free/en/authors/jamin-shin/) · [🧑‍🔬**Seungone Kim** Naver 2 papers here · 1,050 citations](https://md.research.elamur.ai/free/en/authors/seungone-kim/) · [🧑‍🔬**Gunhee Kim** Seoul National University 7 papers here · 1,034 citations](https://md.research.elamur.ai/free/en/authors/gunhee-kim/) · [🧑‍🔬**Sang-Woo Lee** Seoul National University 2 papers here · 988 citations](https://md.research.elamur.ai/free/en/authors/sang-woo-lee/) · [🧑‍🔬**Sangdoo Yun** Seoul National University 2 papers here · 948 citations](https://md.research.elamur.ai/free/en/authors/sangdoo-yun/) · [🧑‍🔬**Hwaran Lee** Naver 2 papers here · 919 citations](https://md.research.elamur.ai/free/en/authors/hwaran-lee/)

[See all 35 people →](https://md.research.elamur.ai/free/en/countries/south-korea/people/)

## Works in our library (44)

Works of its institutions, the most cited first.

1. [**Highly accurate protein structure prediction with AlphaFold**John Jumper, Richard Evans, Alexander Pritzel, et al.*2021 · 43,470 citations*](https://md.research.elamur.ai/free/en/papers/jumper-2021-highly-accurate-protein-structure-prediction/)
2. [**BioBERT: a pre-trained biomedical language representation model for biomedical text mining**Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, et al.*2019 · 8,281 citations*](https://md.research.elamur.ai/free/en/papers/lee-2019-biobert-pre-trained-biomedical-language/)
3. [**ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision**Wonjae Kim, Bokyung Son, Ildoo Kim*2021 · 762 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-vilt-vision-language-transformer-convolution/)
4. [**Modeling Relation Paths for Representation Learning of Knowledge Bases**Yankai Lin, Zhiyuan Liu, Huanbo Luan, et al.*2015 · 695 citations*](https://md.research.elamur.ai/free/en/papers/lin-2015-modeling-relation-paths-representation-learning/)
5. [**OCR-free Document Understanding Transformer**Geewook Kim, Teakgyu Hong, Moonbin Yim, et al.*2021 · 580 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-ocr-free-document-understanding-transformer/)
6. [**REPLUG: Retrieval-Augmented Black-Box Language Models**Weijia Shi, Sewon Min, Michihiro Yasunaga, et al.*2023 · 482 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-replug-retrieval-augmented-black-box/)
7. [**Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity**Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.*2024 · 381 citations*](https://md.research.elamur.ai/free/en/papers/jeong-2024-adaptive-rag-learning-adapt-retrieval/)
8. [**Large Language Models Are Reasoning Teachers**Namgyu Ho, Laura Schmid, Se-Young Yun*2023 · 368 citations*](https://md.research.elamur.ai/free/en/papers/ho-2023-large-language-models-are-reasoning/)
9. [**A Survey on Large Language Models for Code Generation**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
10. [**Averaging Weights Leads to Wider Optima and Better Generalization**Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, et al.*2018 · 355 citations*](https://md.research.elamur.ai/free/en/papers/izmailov-2018-averaging-weights-leads-wider-optima/)
11. [**Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages**Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, et al.*2020 · 333 citations*](https://md.research.elamur.ai/free/en/papers/nekoto-2020-participatory-research-low-resourced-machine/)
12. [**Efficient Dialogue State Tracking by Selectively Overwriting Memory**Sungdong Kim, Sohee Yang, Gyuwan Kim, et al.*2020 · 268 citations*](https://md.research.elamur.ai/free/en/papers/kim-2020-efficient-dialogue-state-tracking-selectively/)
13. [**GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation**Kang Min Yoo, Dongju Park, Jaewook Kang, et al.*2021 · 267 citations*](https://md.research.elamur.ai/free/en/papers/yoo-2021-gpt3mix-leveraging-large-scale-language/)
14. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
15. [**Self-Guided Contrastive Learning for BERT Sentence Representations**Taeuk Kim, Kang Min Yoo, Sang-goo Lee*2021 · 234 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-self-guided-contrastive-learning-bert/)
16. [**Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models**Seungone Kim, Juyoung Suk, Shayne Longpre, et al.*2024 · 220 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-prometheus-2-open-source-language/)
17. [**Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index**Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al.*2019 · 216 citations*](https://md.research.elamur.ai/free/en/papers/seo-2019-real-time-open-domain-question/)
18. [**SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization**Hyunwoo Kim, Jack Hessel, Liwei Jiang, et al.*2023 · 201 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-soda-million-scale-dialogue-distillation/)
19. [**ISO 24617-2: A semantically-based standard for dialogue annotation**Harry Bunt, Jan Alexandersson, Jae-Woong Choe, et al.*2012 · 182 citations*](https://md.research.elamur.ai/free/en/papers/bunt-2012-iso-24617-2-semantically-based/)
20. [**Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/)
21. [**ProsocialDialog: A Prosocial Backbone for Conversational Agents**Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/kim-2022-prosocialdialog-prosocial-backbone-conversational-agents/)
22. [**Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step**Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-symbolic-chain-thought-distillation-small/)
23. [**Knowledge Unlearning for Mitigating Privacy Risks in Language Models**Joel Jang, Dongkeun Yoon, Sohee Yang, et al.*2022 · 126 citations*](https://md.research.elamur.ai/free/en/papers/jang-2022-knowledge-unlearning-mitigating-privacy-risks/)
24. [**Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes**Hyunwoo Kim, Byeongchang Kim, Gunhee Kim*2021 · 90 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-perspective-taking-pragmatics-generating-empathetic/)
25. [**Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness**Hyunwoo Kim, Byeongchang Kim, Gunhee Kim*2020 · 82 citations*](https://md.research.elamur.ai/free/en/papers/kim-2020-will-i-sound-like-me/)

[See all 44 works →](https://md.research.elamur.ai/free/en/countries/south-korea/works/)

## Topics

Topics of its works in our library, with the number of works on each.

[Language models & pretraining (11)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Dialogue systems (5)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Evaluation & benchmarks (4)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning (4)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Question answering (3)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Sentiment & emotion (3)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Multilingual & cross-lingual NLP (3)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Implicature (2)](https://md.research.elamur.ai/free/en/topics/implicature/) · [Coreference resolution (2)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Machine translation (2)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Low-resource languages (2)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Information retrieval & search (2)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Idioms & multiword expressions (2)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · [Discourse analysis (1)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Semantic role labeling (1)](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/) · [Speech & spoken language (1)](https://md.research.elamur.ai/free/en/topics/speech/) · [Knowledge graphs & ontologies (1)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Code & programming languages (1)](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Legal AI (1)](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Semitic languages (1)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Syntax & grammar formalisms (1)](https://md.research.elamur.ai/free/en/topics/syntax-grammar/) · [Bias, fairness & safety (1)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Vision & language (1)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Efficient models & compression (1)](https://md.research.elamur.ai/free/en/topics/efficient-models/)

## Fields

[Linguistics & languages (22)](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [Natural language processing (10)](https://md.research.elamur.ai/free/en/shelves/nlp/) · [Mathematics & statistics (3)](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Machine translation (1)](https://md.research.elamur.ai/free/en/shelves/machine-translation/) · [AI & machine learning (1)](https://md.research.elamur.ai/free/en/shelves/ai/) · [Law (1)](https://md.research.elamur.ai/free/en/shelves/law/)

## Works by year

2020

- [← back to](https://md.research.elamur.ai/free/en/countries/) — countries