  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 $\textbf{Webis-Context-SciSumm-2023}$, a new dataset containing
540K~computer science papers and 4.6M~citances therein.
