PST-Bench: Tracing and Benchmarking the Source of Publications
Fanjin Zhang Kun Cao Yukuo Cen Jifan Yu Da Yin Jie Tang
Tracing the source of research papers is a fundamental yet challenging task
for researchers. The billion-scale citation relations between papers hinder
researchers from understanding the evolution of science efficiently. To date,
there is still a lack of an accurate and scalable dataset constructed by
professional researchers to identify the direct source of their studied papers,
based on which automatic algorithms can be developed to expand the evolutionary
knowledge of science. In this paper, we study the problem of paper source
tracing (PST) and construct a high-quality and ever-increasing dataset
PST-Bench in computer science. Based on PST-Bench, we reveal several intriguing
discoveries, such as the differing evolution patterns across various topics. An
exploration of various methods underscores the hardness of PST-Bench,
pinpointing potential directions on this topic. The dataset and codes have been
available at https://github.com/THUDM/paper-source-trace.