Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP)
algorithms, aims to create concise and accurate summaries, thereby significantly reducing …

Abstract Automatic Text Summarization (ATS) is an important area in Natural Language
Processing (NLP) with the goal of shortening a long text into a more compact version by …

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

Recent pre-trained abstractive summarization systems have started to achieve credible
performance, but a major barrier to their use in practice is their propensity to output …

The “Impression” section of a radiology report is a critical basis for communication between
radiologists and other physicians. Typically written by radiologists, this part is derived from …

Nowadays, most research conducted in the field of abstractive text summarization focuses
on neural-based models alone, without considering their combination with knowledge …

Abstractive summarization models typically learn to capture the salient information from
scratch implicitly. Recent literature adds extractive summaries as guidance for abstractive …

Controllable summarization allows users to generate customized summaries with specified
attributes. However, due to the lack of designated annotations of controlled summaries …

Radiology reports play a critical role in communicating medical findings to physicians. In
each report, the impression section summarizes essential radiology findings. In clinical …

Abstractive summarization systems today produce fluent and relevant output, but often"
hallucinate" statements not supported by the source text. We analyze the connection …