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GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrieval

arXiv 2104.12741 ↗First posted 26 Apr 2021cs.CL cs.LGcited by 39

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Abstract (arXiv)

A major challenge of research on non-English machine reading for question answering (QA) is the lack of annotated datasets. In this paper, we present GermanQuAD, a dataset of 13,722 extractive question/answer pairs. To improve the reproducibility of the dataset creation approach and foster QA research on other languages, we summarize lessons learned and evaluate reformulation of question/answer pairs as a way to speed up the annotation process. An extractive QA model trained on GermanQuAD significantly outperforms multilingual models and also shows that machine-translated training data cannot fully substitute hand-annotated training data in the target language. Finally, we demonstrate the wide range of applications of GermanQuAD by adapting it to GermanDPR, a training dataset for dense passage retrieval (DPR), and train and evaluate the first non-English DPR model.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 12 of its 14 references that are in the map. First posted on arXiv 26 Apr 2021.

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12 of 14 references.

References · 12

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  3. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  4. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,538
  5. 2019Cross-lingual Language Model Pretrainingcited by 1,088
  6. 2019On the Cross-lingual Transferability of Monolingual Representationscited by 575
  7. 2019MLQA: Evaluating Cross-lingual Extractive Question Answeringcited by 339
  8. 2020German's Next Language Modelcited by 144
  9. 2020Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasetscited by 137
  10. 2020FQuAD: French Question Answering Datasetcited by 58
  11. 2019KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehensioncited by 43
  12. 2019SberQuAD -- Russian Reading Comprehension Dataset: Description and Analysiscited by 38

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 4; 2023: 9; 2024: 11; 2025: 9; 2026: 3.

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  1. 2023The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variantscited by 300
  2. 2021Semantic Answer Similarity for Evaluating Question Answering Modelscited by 47
  3. 2024Encoder vs Decoder: Comparative Analysis of Encoder and Decoder Language Models on Multilingual NLU Taskscited by 33
  4. 2022Generative Language Models for Paragraph-Level Question Generationcited by 28
  5. 2024Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddingscited by 20
  6. 2024A Novel Multi-Stage Prompting Approach for Language Agnostic MCQ Generation using GPTcited by 19
  7. 2024Exploring the Capabilities of Prompted Large Language Models in Educational and Assessment Applicationscited by 12
  8. 2023A Practical Toolkit for Multilingual Question and Answer Generationcited by 10
  9. 2021A cost-benefit analysis of cross-lingual transfer methodscited by 7
  10. 2022JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehensioncited by 7
  11. 2023NorQuAD: Norwegian Question Answering Datasetcited by 7
  12. 2025MultiWikiQA: A Reading Comprehension Benchmark in 300+ Languagescited by 7
27 more
  1. 2021A Survey on non-English Question Answering Datasetcited by 5
  2. 2023Fine-tuning and aligning question answering models for complex information extraction taskscited by 5
  3. 2023On the Impact of Cross-Domain Data on German Language Modelscited by 5
  4. 2024TIGQA:An Expert Annotated Question Answering Dataset in Tigrinyacited by 5
  5. 2025New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Modelscited by 5
  6. 2022Pir'a: A Bilingual Portuguese-English Dataset for Question-Answering about the Oceancited by 4
  7. 2025Investigating Task Arithmetic for Zero-Shot Information Retrievalcited by 4
  8. 2023A System for Human-AI collaboration for Online Customer Supportcited by 3
  9. 2025ALoFTRAG: Automatic Local Fine Tuning for Retrieval Augmented Generationcited by 3
  10. 2025A Collection of Question Answering Datasets for Norwegiancited by 2
  11. 2025Evaluating Robustness of LLMs in Question Answering on Multilingual Noisy OCR Datacited by 2
  12. 2022Evaluation of Semantic Answer Similarity Metricscited by 1
  13. 2023AmQA: Amharic Question Answering Datasetcited by 1
  14. 2023German FinBERT: A German Pre-trained Language Modelcited by 1
  15. 2024OMoS-QA: A Dataset for Cross-Lingual Extractive Question Answering in a German Migration Contextcited by 1
  16. 2023Revealing Weaknesses of Vietnamese Language Models Through Unanswerable Questions in Machine Reading Comprehensioncited by 0
  17. 2024Building Efficient and Effective OpenQA Systems for Low-Resource Languagescited by 0
  18. 2024Multilingual De-Duplication Strategies: Applying scalable similarity search with monolingual & multilingual embedding modelscited by 0
  19. 2024Unsupervised Text Representation Learning via Instruction-Tuning for Zero-Shot Dense Retrievalcited by 0
  20. 2024Link, Synthesize, Retrieve: Universal Document Linking for Zero-Shot Information Retrievalcited by 0
  21. 2024A Comparative Study of Text Retrieval Models on DaReCzechcited by 0
  22. 2025How to Tune a Multilingual Encoder Model for Germanic Languages: A Study of PEFT, Full Fine-Tuning, and Language Adapterscited by 0
  23. 2025Arctic-Extract Technical Reportcited by 0
  24. 2025Gamayun's Path to Multilingual Mastery: Cost-Efficient Training of a 1.5B-Parameter LLMcited by 0
  25. 2026Learning Perturbations to Extrapolate Your LLMcited by 0
  26. 2026CroCo: Cross-Lingual Contrastive Preference Tuning on Self-Generationscited by 0
  27. 2026From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sectorcited by 0