State-of-the-art natural language processing (NLP) models are trained on massive training
corpora, and report a superlative performance on evaluation datasets. This survey delves …

To foster the development of pedagogically potent and ethically sound AI-integrated
learning landscapes, it is pivotal to critically explore the perceptions and experiences of the …

The discipline of Automatic Text Summarization (ATS), which is expanding quickly, intends
to automatically create summaries of enormous amounts of text so that readers can save …

This research delves into the latest advancements in Natural Language Processing (NLP)
and their broader implications, challenges, and future directions. With the ever-increasing …

Large text documents are sometimes challenging to understand and time-consuming to
extract vital information from. These issues are addressed by automatic text summarizing …

Learning to read scientific papers critically, which requires first gras** their main ideas
and then raising critical thoughts, is important yet challenging for novice researchers. The …

The rapid progress in deep learning has propelled transformer-based models to the
forefront, establishing them as leading solutions for a multiple NLP tasks. These tasks span …

Transformer-based autoregressive (AR) methods have achieved appealing performance for
varied sequence-to-sequence generation tasks, eg, neural machine translation …

A fitness function is a type of objective function that quantifies the optimality of a solution; the
correct formulation of this function is relevant, in evolutionary-based ATS systems, because it …

Summarizing a text is the process of condensing its content while still maintaining its
essential information. With the abundance of digital information available, summarization …