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Citation sentences (citances) to a reference ar- ticle have been extensively studied for sum- marization tasks. However, citances might not accurately represent the content of the cited article, as they often fail to capture the con- text of the reported findings and can be af- fected by epistemic value drift. Following the intuition behind the TAC (Text Analysis Conference) 2014 Biomedical Summarization track, we propose a system that identifies text spans in the reference article that are related to a given citance. We refer to this problem as citance-reference spans matching. We ap- proach the problem as a retrieval task; in this paper, we detail a comparison of different ci- tance reformulation methods and their combi- nations. While our results show improvement over the baseline (up to 25.9%), their absolute magnitude implies that there is ample room for future improvement.
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