The new era of technology has brought us to the point where it is convenient for people to
share their opinions over an abundance of platforms. These platforms have a provision for …

A major challenge for scaling machine learning is training models to perform tasks that are
very difficult or time-consuming for humans to evaluate. We present progress on this …

Natural Language Processing (NLP) helps empower intelligent machines by enhancing a
better understanding of the human language for linguistic-based human-computer …

With the evolution of the Internet and multimedia technology, the amount of text data has
increased exponentially. This text volume is a precious source of information and knowledge …

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

The problem of Question Answering (QA) has attracted significant research interest for long.
Its relevance to language understanding and knowledge retrieval tasks, along with the …

Since the term first coined in 1999 by Kevin Ashton, the Internet of Things (IoT) has gained
significant momentum as a technology to connect physical objects to the Internet and to …

Abstract Entities and their mentions convey significant semantic information in documents. In
multidocument summarization, the same entity may appear across different documents …

The integration of multi-document pre-training objectives into language models has resulted
in remarkable improvements in multi-document downstream tasks. In this work, we propose …

Multi-document summarization (MDS) aims to generate a summary for a number of related
documents. We propose HGSum—an MDS model that extends an encoder-decoder …