mlsanityData to 7 Oct 2026

Towards Zero-Shot Multilingual Synthetic Question and Answer Generation for Cross-Lingual Reading Comprehension

arXiv 2010.12008 ↗First posted 22 Oct 2020cs.CL cs.AI cs.LGcited by 17

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Abstract (arXiv)

We propose a simple method to generate multilingual question and answer pairs on a large scale through the use of a single generative model. These synthetic samples can be used to improve the zero-shot performance of multilingual QA models on target languages. Our proposed multi-task training of the generative model only requires the labeled training samples in English, thus removing the need for such samples in the target languages, making it applicable to far more languages than those with labeled data. Human evaluations indicate the majority of such samples are grammatically correct and sensible. Experimental results show our proposed approach can achieve large gains on the XQuAD dataset, reducing the gap between zero-shot and supervised performance of smaller QA models on various languages.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Oct 2020.

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Citing papers per year: 2021: 2; 2022: 5; 2023: 3; 2024: 6; 2025: 1.

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  1. 2024Best Practices and Lessons Learned on Synthetic Datacited by 104
  2. 2022Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generationcited by 62
  3. 2021One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrievalcited by 46
  4. 2022QAmeleon: Multilingual QA with Only 5 Examplescited by 25
  5. 2023PAXQA: Generating Cross-lingual Question Answering Examples at Training Scalecited by 10
  6. 2024Prompting-based Synthetic Data Generation for Few-Shot Question Answeringcited by 9
  7. 2025AskQE: Question Answering as Automatic Evaluation for Machine Translationcited by 7
  8. 2021Cross-Lingual Open-Domain Question Answering with Answer Sentence Generationcited by 6
  9. 2022Combining Data Generation and Active Learning for Low-Resource Question Answeringcited by 5
  10. 2022IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehensioncited by 4
  11. 2023PrimeQA: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Developmentcited by 4
  12. 2023A Unified Framework for Generative Data Augmentation: A Comprehensive Surveycited by 4
5 more
  1. 2024GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learningcited by 3
  2. 2022ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering Systemcited by 1
  3. 2024SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languagescited by 1
  4. 2024Cross-lingual Transfer for Automatic Question Generation by Learning Interrogative Structures in Target Languagescited by 1
  5. 2024SandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrievalcited by 0