This paper reviews the state-of-the-art of language models architectures and strategies for"
complex" question-answering (QA, CQA, CPS) with a focus on hybridization. Large …

While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …

In recent years, deep learning has revolutionized natural language processing (NLP) by
enabling the development of models that can learn complex representations of language …

Query-focused summarization (QFS) is a challenging task in natural language processing
that generates summaries to address specific queries. The broader field of Generative …

Abstract Knowledge transfer is investigated in various natural language processing tasks
except cross-domain constituency parsing. In this paper, we leverage heterogeneous data to …

Abstract Query-Focused Summarization (QFS) aims to generate summaries from source
documents that can answer specific queries. Although the QFS task has gained increasing …

This study examines the potential of integrating Learning-to-Rank (LTR) with Query-focused
Summarization (QFS) to enhance the summary relevance via content prioritization. Using a …

Text summarization has been an important task for natural language processing. It aims to
compress the source document (s) into a more concise version that covers the most …

My research goal in this dissertation is to develop neural summarization methods for better
adaptation to domain-specific corpora with a focus on Clinical Notes, Scientific Documents …