Community-Driven Comprehensive Scientific Paper Summarization: Insight from cvpaper.challenge
This addresses the literature survey burden for non-native English-speaking researchers in computer vision, though it is incremental as it applies an existing community-driven approach to a specific domain.
The paper tackles the problem of the rapid increase in scientific papers burdening researchers, especially non-native speakers, by organizing a group of non-native English speakers to write summaries of 2,000 papers from the Conference on Computer Vision and Pattern Recognition in 2019 and 2020, with quantitative analysis showing that participants could summarize a wide range of papers without reading unrelated ones.
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.