ACM-CR: A Manually Annotated Test Collection for Citation Recommendation
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Abstract (arXiv)
Citation recommendation is intended to assist researchers in the process of searching for relevant papers to cite by recommending appropriate citations for a given input text. Existing test collections for this task are noisy and unreliable since they are built automatically from parsed PDF papers. In this paper, we present our ongoing effort at creating a publicly available, manually annotated test collection for citation recommendation. We also conduct a series of experiments to evaluate the effectiveness of content-based baseline models on the test collection, providing results for future work to improve upon. Our test collection and code to replicate experiments are available at https://github.com/boudinfl/acm-cr
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 17 Aug 2021.
Builds on
3 of 9 references.
References · 3
- 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
- 2020Citation Recommendation: Approaches and Datasetscited by 36
- 2020HybridCite: A Hybrid Model for Context-Aware Citation Recommendationcited by 7
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Citing papers per year: 2025: 1.
1 paper.