Community-Driven Comprehensive Scientific Paper Summarization: Insight from cvpaper.challenge

TL;DR

This paper presents a community-driven approach where volunteers summarize conference papers to help researchers, especially non-native speakers, efficiently grasp key insights from a large volume of scientific literature.

Contribution

It introduces a collaborative summarization method for scientific papers, demonstrating effective coverage and participant engagement in summarizing 2,000 papers at CVPR 2019 and 2020.

Findings

Participants focused on papers aligned with their interests.

Summarization covered a broad range of papers without unrelated topics.

The approach alleviates the burden of literature review for researchers.

Abstract

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.