XQuAD Dataset Papers With Code
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Last updated 17 fevereiro 2025
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XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German, Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, and Hindi. Consequently, the dataset is entirely parallel across 11 languages.
Figure A2: Truncated distribution of usages per dataset in PWC
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PDF] JaQuAD: Japanese Question Answering Dataset for Machine
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image171.png
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How to Answer Questions with Machine Learning
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MLQA Dataset Papers With Code
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How to Build an Open-Domain Question Answering System?
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The OIG Dataset
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Papers With Code Machine Learning Papers and Code Free Resource
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XQuAD Dataset Papers With Code
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How to Answer Questions with Machine Learning
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Snorkel AI researchers present 18 papers at NeurIPS 2023
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An Introduction to Papers With Code: What It is And How to Use It
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The OIG Dataset
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How to train YOLOv8 on a custom Dataset — Picsellia
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iFLYTEK & HIT Reading Comprehension Model Betters Humans, Tops
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