πŸ“„
EDGAR-CORPUS: Billions of Tokens Make The World Go Round paper by Independent / Community
⭐ 68.7
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Paper

EDGAR-CORPUS: Billions of Tokens Make The World Go Round

by Independent / Community 00b2de0153e32de9b86da772ad5cdc2b0cac1002
Free2AITools Nexus Index
68.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 84
P: Popularity 60
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

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 e...

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Semantic Scholar 47 Citations
Paper Information Summary
Entity Passport
Registry ID 00b2de0153e32de9b86da772ad5cdc2b0cac1002
License ArXiv
Provider semantic_scholar
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Cite this paper

Academic & Research Attribution

BibTeX 
@misc{00b2de0153e32de9b86da772ad5cdc2b0cac1002,
  author = {Unknown},
  title = {EDGAR-CORPUS: Billions of Tokens Make The World Go Round Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00b2de0153e32de9b86da772ad5cdc2b0cac1002}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). EDGAR-CORPUS: Billions of Tokens Make The World Go Round [Paper]. Free2AITools. https://api.semanticscholar.org/00b2de0153e32de9b86da772ad5cdc2b0cac1002

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Full Specifications [+]

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 84
Popularity (P) 60
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for EDGAR-CORPUS: Billions of Tokens Make The World Go Round: Authority (A:84), Popularity (P:60), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data

πŸ“ Executive Summary

"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 e..."

❝ Cite Node 

@article{Unknown2026EDGAR-CORPUS:,
  title={EDGAR-CORPUS: Billions of Tokens Make The World Go Round},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

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πŸ“Š Research Signals

πŸ“ˆ47CitationsSemantic Scholar
πŸ›οΈ84AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈautomation workflowField

🏷️ Research Topics

embeddings
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πŸ†” Identity & Source

source
semantic_scholar
author
Unknown
license
ArXiv
tags
paper, research, academic

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

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citations
47

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