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KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehension

arXiv 1909.07005 ↗First posted 16 Sep 2019cs.CLcited by 43

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Abstract (arXiv)

Machine Reading Comprehension (MRC) is a task that requires machine to understand natural language and answer questions by reading a document. It is the core of automatic response technology such as chatbots and automatized customer supporting systems. We present Korean Question Answering Dataset(KorQuAD), a large-scale Korean dataset for extractive machine reading comprehension task. It consists of 70,000+ human generated question-answer pairs on Korean Wikipedia articles. We release KorQuAD1.0 and launch a challenge at https://KorQuAD.github.io to encourage the development of multilingual natural language processing research.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Sep 2019.

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Citing papers per year: 2021: 13; 2022: 10; 2023: 5; 2024: 7; 2025: 5; 2026: 3.

43 papers.

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  1. 2023A Comprehensive Overview of Large Language Modelscited by 648
  2. 2021KLUE: Korean Language Understanding Evaluationcited by 114
  3. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  4. 2024KMMLU: Measuring Massive Multitask Language Understanding in Koreancited by 91
  5. 2022On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Modelcited by 81
  6. 2021What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformerscited by 76
  7. 2024CLIcK: A Benchmark Dataset of Cultural and Linguistic Intelligence in Koreancited by 66
  8. 2022Language Modelling with Pixelscited by 55
  9. 2021GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrievalcited by 39
  10. 2024CaLMQA: Exploring culturally specific long-form question answering across 23 languagescited by 31
  11. 2022Generative Language Models for Paragraph-Level Question Generationcited by 28
  12. 2021English Machine Reading Comprehension Datasets: A Surveycited by 26
31 more
  1. 2022Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resourcescited by 25
  2. 2023An Efficient Multilingual Language Model Compression through Vocabulary Trimmingcited by 20
  3. 2022PQuAD: A Persian Question Answering Datasetcited by 14
  4. 2021ParaShoot: A Hebrew Question Answering Datasetcited by 12
  5. 2023A Practical Toolkit for Multilingual Question and Answer Generationcited by 10
  6. 2021Sentence Extraction-Based Machine Reading Comprehension for Vietnamesecited by 9
  7. 2021Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Taskscited by 8
  8. 2024Accelerating Multilingual Language Model for Excessively Tokenized Languagescited by 8
  9. 2022VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehensioncited by 7
  10. 2023NorQuAD: Norwegian Question Answering Datasetcited by 7
  11. 2021A Survey on non-English Question Answering Datasetcited by 5
  12. 2024TIGQA:An Expert Annotated Question Answering Dataset in Tigrinyacited by 5
  13. 2022LittleBird: Efficient Faster & Longer Transformer for Question Answeringcited by 4
  14. 2021A Survey on Awesome Korean NLP Datasetscited by 3
  15. 2022Korean-Specific Dataset for Table Question Answeringcited by 3
  16. 2025ALoFTRAG: Automatic Local Fine Tuning for Retrieval Augmented Generationcited by 3
  17. 2026K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contextscited by 3
  18. 2022XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Sourcecited by 2
  19. 2025A Collection of Question Answering Datasets for Norwegiancited by 2
  20. 2021Improving Cross-Lingual Reading Comprehension with Self-Trainingcited by 1
  21. 2022Question Answering and Question Generation for Finnishcited by 1
  22. 2025Finnish SQuAD: A Simple Approach to Machine Translation of Span Annotationscited by 1
  23. 2021Structured Pattern Pruning Using Regularizationcited by 0
  24. 2021DPRK-BERT: The Supreme Language Modelcited by 0
  25. 2023Integrating Image Features with Convolutional Sequence-to-sequence Network for Multilingual Visual Question Answeringcited by 0
  26. 2024Building Efficient and Effective OpenQA Systems for Low-Resource Languagescited by 0
  27. 2024Building a Rich Dataset to Empower the Persian Question Answering Systemscited by 0
  28. 2025Making Sense of Korean Sentences: A Comprehensive Evaluation of LLMs through KoSEnd Datasetcited by 0
  29. 2025Beyond Line-Level Filtering for the Pretraining Corpora of LLMscited by 0
  30. 2026FastSLM: Hierarchical Temporal Abstraction for Efficient Long-Form Speech Adaptationcited by 0
  31. 2026KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacterscited by 0