Paragraph-level Citation Recommendation based on Topic Sentences as
  Queries
Zoran Medić Jan Šnajder
Citation recommendation (CR) models may help authors find relevant articles
at various stages of the paper writing process. Most research has dealt with
either global CR, which produces general recommendations suitable for the
initial writing stage, or local CR, which produces specific recommendations
more fitting for the final writing stages. We propose the task of
paragraph-level CR as a middle ground between the two approaches, where the
paragraph's topic sentence is taken as input and recommendations for citing
within the paragraph are produced at the output. We propose a model for this
task, fine-tune it using the quadruplet loss on the dataset of ACL papers, and
show improvements over the baselines.