Despite the progress that has been achieved in over 50 years of research, automatic text
summarization systems are still far from perfect, posing many challenges to the researchers …

Text summarization is the research area aiming at creating a short and condensed version
of the original document, which conveys the main idea of the document in a few words. This …

Conversational analysis plays an important role in the development of simulation devices for
the training of health professionals (doctors, nurses). Our goal is to develop an original …

Nowadays, neural text generation has made tremendous progress in abstractive
summarization tasks. However, most of the existing summarization models take in the whole …

Update summarization is a relatively recent summarization task concerned with creating a
short summary from news articles, assuming the user has already read a number of previous …

Currently, the explosive growth of the information available on the Internet makes automatic
text summarization systems increasingly important. A particularly relevant challenge is the …

Abstract Cross-Level Semantic Similarity (CLSS) is a measure of the level of semantic
overlap between texts of different lengths. Although this problem was formulated almost a …

In this paper, we investigate the efficacy of various cutting-edge models for update
summarization on the TAC 2009 dataset. To construct abstractive and extractive summaries …

Automatic document summarization aims at creating a shorter version of one or more
documents to help users digest large amounts of information more easily by highlighting the …

Update summarization aims at automatically producing a summary for a collection of texts
for a reader that has already read some previous texts about the subject of interest. It is a …