XQuAD Dataset Papers With Code
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Descrição
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.
How to Answer Questions with Machine Learning
XQA: A Cross-lingual Open-domain Question Answering Dataset
Papers with code or without code? Impact of GitHub repository
ACL Best Paper: Tricky Stanford DataSet Adds Questions That Don't
Token-level statistics of the constructed datasets. Average Length
bigscience/P3 · Datasets at Hugging Face
Figure A2: Truncated distribution of usages per dataset in PWC
XQA Dataset Papers With Code
How to Answer Questions with Machine Learning
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SQuAD model sentence relation and deep semantics error
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