Datasets › MLQA
MLQA (MultiLingual Question Answering)
MLQA (MultiLingual Question Answering) is a benchmark dataset for evaluating cross-lingual question answering performance. MLQA consists of over 5K extractive QA instances (12K in English) in SQuAD format in seven languages - English, Arabic, German, Spanish, Hindi, Vietnamese and Simplified Chinese. MLQA is highly parallel, with QA instances parallel between 4 different languages on average.
Source: Facebook Research Image Source: https://github.com/facebookresearch/mlqa
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Cross-Lingual Question Answering | MLQA | ByT5 XXL F1 71.6 | ByT5: Towards a token-free future with pre-trained... | huggingface/transformers +4 | 3 | Compare |
Papers archive 2025-07-28
2 shown of 2 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 167. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| ByT5: Towards a token-free future with pre-trained byte-to-byte models | 5 | 1 | 28 May 2021 | ran 0 of 6 samples (6 unverified) |
| Rethinking embedding coupling in pre-trained language models | 4 | 2 | 24 Oct 2020 | not harvested |
Dataset loaders archive 2025-07-28
5 loaders as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- MLQA
1 variant name, as the archive lists them.
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