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.

Papers With Code (Free Resource of Machine Learning Papers and

Multi-domain Multilingual Question Answering

XQuAD Dataset Papers With Code

SQuAD2.0 Benchmark (Question Answering)

GitHub - google-deepmind/xquad

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

How to train YOLOv8 on a custom Dataset — Picsellia

Papers with code or without code? Impact of GitHub repository

PDF] JaQuAD: Japanese Question Answering Dataset for Machine