Summarization, is to reduce the size of the document while preserving the meaning, is one
of the most researched areas among the Natural Language Processing (NLP) community …

The task of automatic document summarization aims at generating short summaries for
originally long documents. A good summary should cover the most important information of …

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 …

With the rapid development and popularization of Internet and mobile communication
technologies, text data mining has attracted much attention. In particular, with the wide use …

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 …

We present ClidSum, a benchmark dataset for building cross-lingual summarization systems
on dialogue documents. It consists of 67k+ dialogue documents from two subsets (ie …

In this paper, we investigate the sentence summarization task that produces a summary from
a source sentence. Neural sequence-to-sequence models have gained considerable …

Current state-of-the-art cross-lingual summarization models employ multi-task learning
paradigm, which works on a shared vocabulary module and relies on the self-attention …