Paragraph-level Citation Recommendation based on Topic Sentences as Queries
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 29 references that are in the map. First posted on arXiv 20 May 2023.
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17 of 29 references.
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5 more
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