PST-Bench: Tracing and Benchmarking the Source of Publications
This addresses the difficulty for researchers in efficiently understanding science evolution due to billion-scale citation relations, though it is incremental as it builds on existing data collection efforts.
The paper tackles the problem of tracing the source of research papers by constructing PST-Bench, a high-quality dataset in computer science, revealing differing evolution patterns across topics and highlighting the challenge of the task.
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.