In recent years, the volume of textual data has rapidly increased, which has generated a
valuable resource for extracting and analysing information. To retrieve useful knowledge …

Automatic text summarization essentially condenses a long document into a shorter format
while preserving its information content and overall meaning. It is a potential solution to the …

The increasing usage of the Internet and social networks has produced a significant amount
of online textual data. These online textual data led to information overload and redundancy …

Automatic text summarization (ATS) is a method to condense a long size text document into
abridging form by enveloping all the primary information and central theme. Numerous ATS …

We construct Global Voices, a multilingual dataset for evaluating cross-lingual
summarization methods. We extract social-network descriptions of Global Voices news …

AI and NLP publication venues have increasingly encouraged researchers to reflect on
possible ethical considerations, adverse impacts, and other responsible AI issues their work …

Meetings play a critical infrastructural role in the coordination of work. In recent years, due to
shift to hybrid and remote work, more meetings are moving to online Computer Mediated …

Trajectory generation for biped robots is very complex due to the challenge posed by real-
world uneven terrain. To address this complexity, this paper proposes a data-driven Gait …

Query‐focused multi‐document summarization (Qf‐MDS) is a sub‐task of automatic text
summarization that aims to extract a substitute summary from a document cluster of the …

Domain adaptation on text summarization task is always challenging, which is caused by the
lack of annotated data in the target domain. Previous methodologies focused more on …