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Found 7 papers, 5 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.
CoDesc: A Large Code-Description Parallel Dataset
In this study, we present CoDesc -- a large parallel dataset composed of 4. 2 million Java methods and natural language descriptions.
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Text2App: A Framework for Creating Android Apps from Text Descriptions
We overcome this limitation by transforming natural language into an abstract intermediate formal language representing an application with a substantially smaller number of tokens.
BERT2Code: Can Pretrained Language Models be Leveraged for Code Search?
In this work, we leverage the efficacy of these embedding models using a simple, lightweight 2-layer neural network in the task of semantic code search.
BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding
As a bi-product of the standard NLU benchmarks, we introduce a new downstream dataset on natural language inference (NLI) and show that BanglaBERT outperforms previous state-of-the-art results on all tasks by up to 3. 5%.
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.
Early Prediction for Merged vs Abandoned Code Changes in Modern Code Reviews
In our empirical study on the 146, 612 code changes from the three software projects, we find that (1) The new features like reviewer dimensions that are introduced in PredCR are the most informative.