Community-Driven Comprehensive Scientific Paper Summarization: Insight from cvpaper.challenge
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Abstract (arXiv)
The present paper introduces a group activity involving writing summaries of conference proceedings by volunteer participants. The rapid increase in scientific papers is a heavy burden for researchers, especially non-native speakers, who need to survey scientific literature. To alleviate this problem, we organized a group of non-native English speakers to write summaries of papers presented at a computer vision conference to share the knowledge of the papers read by the group. We summarized a total of 2,000 papers presented at the Conference on Computer Vision and Pattern Recognition, a top-tier conference on computer vision, in 2019 and 2020. We quantitatively analyzed participants' selection regarding which papers they read among the many available papers. The experimental results suggest that we can summarize a wide range of papers without asking participants to read papers unrelated to their interests.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 9 references that are in the map. First posted on arXiv 17 Mar 2022.
Builds on
7 of 9 references.
References · 7
- 2018A Discourse-Aware Attention Model for Abstractive Summarization of Long Documentscited by 478
- 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 430
- 2020TLDR: Extreme Summarization of Scientific Documentscited by 136
- 2019ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networkscited by 73
- 2017A Supervised Approach to Extractive Summarisation of Scientific Paperscited by 33
- 2019TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talkscited by 20
- 2019The CL-SciSumm Shared Task 2018: Results and Key Insightscited by 9
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