Scholarly Document

Research on scholarly documents focuses on improving access to and understanding of the vast and growing body of academic literature. Current efforts leverage natural language processing (NLP) techniques, including large language models (LLMs) and knowledge graphs, to enhance search, summarization, and information extraction from scholarly publications. These advancements aim to address information overload, improve the efficiency of literature reviews, and facilitate knowledge discovery across disciplines, ultimately benefiting researchers and accelerating scientific progress. Furthermore, research is actively addressing the ethical implications of AI-assisted writing and the detection of AI-generated content in academic work.