While recent work in abstractive summarization has resulted in higher scores in automatic
metrics, there is little understanding on how these systems combine information taken from …

Sentence fusion is the task of joining several independent sentences into a single coherent
text. Current datasets for sentence fusion are small and insufficient for training modern …

Multi-text applications, such as multi-document summarization, are typically required to
model redundancies across related texts. Current methods confronting consolidation …

Sentence fusion—the merging of sentences containing similar information—has been
shown to be useful in an abstractive summarization context. We present a new dataset of …

Fusing sentences containing disparate content is a remarkable human ability that helps
create informative and succinct summaries. Such a simple task for humans has remained …

The present work proposes a scheme for multi-document abstractive text summarization
using node-aligned Word Graph based representation of clustered sentences. In the first …

Fast alignment is essential for many natural language tasks. But in the setting of
monolingual alignment, previous work has not been able to align more than one sentence …

The lack of multi-document based models and the inaccuracy in representing multiple long
documents into a fixed size vector inspired us to solve abstractive multi-document …