Recently, Jiani Huang, a 2021-grade master student of our School, published a summary article entitled with From Detection to Application: Recent Advances in Understanding Scientific Tables and Figures in ACM Computing Surveys. Jiani Huang is the first author of the article.

The instructor of this article is Wei Lu, Professor at our School, Fengchang Yu, post-doctoral fellow at our School, and Haihua Chen, Assistant Professor at the University of North Texas. This was the first time that teachers and students of our School published article in this journal as the first author and corresponding author.

In academic literature, tables and figures often present information in a structured and visualized way. Understanding these tables and figures is very important for downstream tasks such as academic retrival, and academic document understanding. This article combs the whole process of academic tables and figures detection, structure analysis, semantic understanding and downstream application, and analyzes the benchmark data set, the latest technology and its advantages and disadvantages in detail, pointing out the challenges faced by the current field and the potential development direction of future research. This was the first article that comprehensively summarizes the understanding of academic tables and figures, covering all aspects from detection to application, which can offer reference for researchers in related fields and promote the mining and application development of tables and figures in academic document.

ACM Computing Surveys (CSUR) is a well-known comprehensive publication in the computer science field. Since its inception in 1969, it has been highly concerned and recognized by top scholars around the world, and has outstanding impact in international academic community. According to the up-to-date data, the impact factor of CSUR is 16.6, ranking third among 111 journals in the field of theory and method of computer science.