On the Use of ArXiv as a Dataset
The arXiv has collected 1.5 million pre print articles over 28 years, hosting literature from scientific fields including Physics, Mathematics, and Computer Science. Each pre print features text, figures, authors, citations, categories, and other metadata. These rich, multi modal features, combined with the natural graph structure created by citation, affiliation, and co authorship makes the arXiv an exciting candidate for benchmarking next generation models. Here we take the first necessary steps toward this goal, by providing a pipeline which standardizes and simplifies access to the arXiv's publicly available data. We use this pipeline to extract and analyze a 6.7 million edge citation graph, with an 11 billion word corpus of full text research articles. We present some baseline classification results, and motivate application of more exciting generative graph models.
ArXiv