Redundancy-aware extractive summarization systems score the redundancy of the
sentences to be included in a summary either jointly with their salience information or …

Labeling large amounts of extractive summarization data is often prohibitive expensive due
to time, financial, and expertise constraints, which poses great challenges to incorporating …

Historically speaking, the German legal language is widely neglected in NLP research,
especially in summarization systems, as most of them are based on English newspaper …

Automated summarization of clinical texts can reduce the burden of medical professionals.“
Discharge summaries” are one promising application of the summarization, because they …

Standard extractive systems suffer from the lack of gold training signals since existing
corpora solely provide document and human-written summary pairs while disregarding …

Researchers consistently publish articles to contribute to science. However, it has become
difficult to understand the terms employed in the document along with the way the semantic …

The sentence-level extracted summary is inevitably mixed with redundant information due to
the uninformative phrases or detailed expressions mixed in it. The extraction of fine-grained …

Extractive text summarization is a well-studied downstream task of natural language
processing that aims to select sentences as a summary of the document's critical …

Reviews of songs play an important role in online music service platforms. Prior research
shows that users can make quicker and more informed decisions when presented with …

With the continuous development of educational informatization, more and more emerging
technologies are applied in teaching activities. These technologies provide massive and …