2023/11/04 by Shahbaz Syed, Ahmad Dawar Hakimi, Syed, Shahbaz +5 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Semantic Web and Ontologies #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2311.02408
openalex publication_date 2023/11/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Current approaches to automatic summarization of scientific papers generate informative summaries in the form of abstracts. However, abstracts are not intended to show the relationship between a paper and the references cited in it. We propose a new contextualized summarization approach that can generate an informative summary conditioned on a given sentence containing the citation of a reference (a so-called "citance"). This summary outlines the content of the cited paper relevant to the citation location. Thus, our approach extracts and models the citances of a paper, retrieves relevant passages from cited papers, and generates abstractive summaries tailored to each citance. We evaluate our approach using Webis-Context-SciSumm-2023, a new dataset containing 540K~computer science papers and 4.6M~citances therein.