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.
XQuAD Dataset  Papers With Code
How to Answer Questions with Machine Learning
XQuAD Dataset  Papers With Code
XQA: A Cross-lingual Open-domain Question Answering Dataset
XQuAD Dataset  Papers With Code
Papers with code or without code? Impact of GitHub repository
XQuAD Dataset  Papers With Code
ACL Best Paper: Tricky Stanford DataSet Adds Questions That Don't
XQuAD Dataset  Papers With Code
Token-level statistics of the constructed datasets. Average Length
XQuAD Dataset  Papers With Code
bigscience/P3 · Datasets at Hugging Face
XQuAD Dataset  Papers With Code
Figure A2: Truncated distribution of usages per dataset in PWC
XQuAD Dataset  Papers With Code
XQA Dataset Papers With Code
XQuAD Dataset  Papers With Code
How to Answer Questions with Machine Learning
XQuAD Dataset  Papers With Code
Challenges and Opportunities in NLP Benchmarking
XQuAD Dataset  Papers With Code
PGPS9K Dataset Papers With Code
XQuAD Dataset  Papers With Code
SQuAD model sentence relation and deep semantics error
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