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.

Results reported on TrecQA, WikiQA, and SQUAD-Sent datasets. SQUAD

The OIG Dataset

Spoken-SQuAD Dataset

How SIGNAL IDUNA operationalizes machine learning projects on AWS

🤗 Datasets: A community library for natural language processing

An example from the SQuAD dataset. Evidences needed for the answer

GitHub - pallavrajsahoo/Question-Answering-System-with-SQuAD

End to End Question-Answering System Using NLP and SQuAD Dataset

Sample from the GermanDPR dataset. 0.0 0.2 0.4 0.6 0.8 1.0 0.4 0.5

Nlakh Dataset Papers With Code

Papers with code or without code? Impact of GitHub repository

XQuAD Benchmark (Cross-Lingual Question Answering)

VCTK Dataset - Machine Learning Datasets