Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: EDGAR-CORPUS: Billions of Tokens Make The World Go Round   We release EDGAR-CORPUS, a novel corpus comprising annual reports from all
the publicly traded companies in the US spanning a period of more than 25
years. To the best of our knowledge, EDGAR-CORPUS is the largest financial NLP
corpus available to date. All the reports are downloaded, split into their
corresponding items (sections), and provided in a clean, easy-to-use JSON
format. We use EDGAR-CORPUS to train and release EDGAR-W2V, which are WORD2VEC
embeddings for the financial domain. We employ these embeddings in a battery of
financial NLP tasks and showcase their superiority over generic GloVe
embeddings and other existing financial word embeddings. We also open-source
EDGAR-CRAWLER, a toolkit that facilitates downloading and extracting future
annual reports.

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The categories of this paper are: eess
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The categories of this paper are: stat
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The categories of this paper are: plasm-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: funct-an
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The categories of this paper are: hep-th
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The categories of this paper are: math
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The categories of this paper are: hep-ex
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The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
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The categories of this paper are: q-bio
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The categories of this paper are: hep-lat
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The categories of this paper are: cond-mat
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The categories of this paper are: ao-sci
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The categories of this paper are: supr-con
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The categories of this paper are: physics