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Found 3 papers, 3 papers with code
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages
XL-Sum induces competitive results compared to the ones obtained using similar monolingual datasets: we show higher than 11 ROUGE-2 scores on 10 languages we benchmark on, with some of them exceeding 15, as obtained by multilingual training.
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla
In this work, we introduce BanglaBERT, a BERT-based Natural Language Understanding (NLU) model pretrained in Bangla, a widely spoken yet low-resource language in the NLP literature.
Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation
With the segmenter and the two methods combined, we compile a high-quality Bengali-English parallel corpus comprising of 2. 75 million sentence pairs, more than 2 million of which were not available before.
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