Wolfram Language Paclet Repository
Community-contributed installable additions to the Wolfram Language
ArXivExplore helps the deep data analysis of all research articles on ArXiv
Contributed by: Daniele Gregori
ArXivExplore helps the deep data analysis of all 2.6M physics, math, cs, etc. articles on ArXiv, providing functionality for e.g. title/abstract word statistics; TeX source/formulae and citations dissection; NNs for classification or recommendation; LLM automated concept definitions and author reports.
To install this paclet in your Wolfram Language environment,
evaluate this code:
PacletInstall["DanieleGregori/ArXivExplore"]
To load the code after installation, evaluate this code:
Needs["DanieleGregori`ArXivExplore`"]
The first article ever on ArXiv:
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A DateListPlot showing the trends in the most popular title words in theoretical physics category (hep-th):
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All the 50 most common 2-neighbour title words on the whole ArXiv, ever:
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Let us also show an author's citations graph, with the tooltip indicating the articles ids:
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The dimensions whole ArXiv dataset (at the end of July 2024):
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Let us create a super-database with all computer science "cs" type primary or cross-list categories:
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and then let us visualize the most frequent and less frequent title words:
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Let us compute the 4 most frequent categories, with their meaning:
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Using only titles and abstracts, we can train a NN to classify different categories:
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Even with a basic 17 minutes training on laptop CPU, we obtain 98% accuracy:
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We could even classify authors within the same category, with ArXivClassifyAuthorNet.
Extracting TEX introduction:
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also TEX formulae:
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Explain a technical concept using an article introduction and LLMSynthesize:
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Let us visualize all authors with more than 7 papers, in primary category "cs.NA":
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Let us pick a random author among them and use LLM functionality to explain his overall work:
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Wolfram Language Version 14