Citation Block Determination Using Textual Coherence

Abstract

Detecting the boundaries of citations in the running text of research papers is an important task for research paper summarisation, idea attribution, sentiment analysis, and other citation-based analysis research. Recently, detecting non-explicit citing sentences has garnered some attention, but can still be seen as in its infancy. We define this task as citation block determination (CBD). In this paper we propose and investigate the effects of various types of textual coherence on CBD, positing that it is a crucial aspect of identifying citation blocks, as it is fundamental to the composition of citations themselves. We demonstrate promising results, with our method outperforming previous state-of-the-art on F1 by a large margin, with an improvement in both precision and recall, and further provide an in-depth error analysis and discussion of why this is the case.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 14 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.