XQuAD Dataset Papers With Code

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.

TyDiQA-GoldP Dataset

LSP Dataset - Machine Learning Datasets

Many Languages, One Deep Learning Model

Automatic Spanish Translation of SQuAD Dataset for Multi-lingual

MLQA Dataset Papers With Code

Papers + Code - MIT-IBM Watson AI Lab

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SQuAD2.0 Benchmark (Question Answering)

An Introduction to Papers With Code: What It is And How to Use It

SQuAD model sentence relation and deep semantics error

ACL Best Paper: Tricky Stanford DataSet Adds Questions That Don't

Sensitivity to parameter choices on the Kazer et al.⁶ dataset and