CiteArXiv: A Citation-enriched Dataset and Heterogeneous Graph-based Model for Scientific Articles Summarization
Year: 2025
Type: conference-paper
Abstract: The exponential growth of scientific publications creates challenges for researchers in processing information. To improve summarization quality, we present CiteArXiv, a large-scale citation-enriched extension of the ArXiv dataset, where each paper is paired with its citation sentences. We further propose a heterogeneous graph model that integrates internal content and external citation context, using elementary discourse units (EDUs) as extraction granularity. Experimental results show that combining internal and external knowledge enhances scientific summarization performance.
Authors: Quoc-An Nguyen, Xuan-Hung Le, Thi-Minh-Thu Vu, Hoang-Quynh Le
Institution: VNU University of Engineering and Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410636996