Bi-lingual mT5

Reported on 4 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Adversarial2 results

Text GenerationonXAlign
BLEU4· 2022-09-22
25.88
best: 29.27 (Fact-aware embedding with mT5)
XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages arXiv:2209.11252
Text GenerationonXAlign
METEOR· 2022-09-22
50.91
best: 53.64 (Fact-aware embedding with mT5)
XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages arXiv:2209.11252

Natural Language Processing2 results

Data-to-Text GenerationonXAlign
BLEU4· 2022-09-22
25.88
best: 29.27 (Fact-aware embedding with mT5)
XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages arXiv:2209.11252
Data-to-Text GenerationonXAlign
METEOR· 2022-09-22
50.91
best: 53.64 (Fact-aware embedding with mT5)
XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages arXiv:2209.11252