We introduce WikiLingua, a large-scale, multilingual dataset for the evaluation of
crosslingual abstractive summarization systems. We extract article and summary pairs in 18 …

Cross-lingual summarization is the task of generating a summary in one language (eg,
English) for the given document (s) in a different language (eg, Chinese). Under the …

We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. Obtained
from online newspapers, it contains 1.5 M+ article/summary pairs in five different languages …

In this work we focus on transferring supervision signals of natural language generation
(NLG) tasks between multiple languages. We propose to pretrain the encoder and the …

Cross-lingual summarization (CLS) is the task to produce a summary in one particular
language for a source document in a different language. Existing methods simply divide this …

The goal of the cross-lingual summarization (CLS) is to convert a document in one language
(eg, English) to a summary in another one (eg, Chinese). Essentially, the CLS task is the …

Parallel cross-lingual summarization data is scarce, requiring models to better use the
limited available cross-lingual resources. Existing methods to do so often adopt sequence-to …

Cross-lingual summarization is the task of generating a summary in one language given a
text in a different language. Previous works on cross-lingual summarization mainly focus on …

Recent work has shown that pre-trained Transformers obtain remarkable performance on
many natural language processing tasks, including automatic summarization. However …

Text encoding is one of the most important steps in Natural Language Processing (NLP). It
has been done well by the self-attention mechanism in the current state-of-the-art …