Basic Examples (4) 

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 100 most common 2-neighbour title words on the whole ArXiv, ever:

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1956.861427`

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Let us also show an author's citations graph, with the tooltip indicating the articles ids:

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Scope (12) 

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:

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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 15 minutes training on laptop CPU, we obtain 95% accuracy:

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We could even to 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:

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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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