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S2ORC ArXiv
A subset of the Semantic Scholar Open Research Corpus (S2ORC) filtered to ArXiv papers. Contains 2.58 million parsed scientific papers with full text, abstracts, structured sections, figures, and citation metadata.
Dataset Summary
| Statistic | Value |
|---|---|
| Total papers | 2,579,762 |
| Total size | ~266 GB |
| Format | Parquet |
| Split | train |
Dataset Structure
Content Fields
| Field | Type | Description |
|---|---|---|
title |
string | Paper title |
abstract |
string | Paper abstract |
text |
string | Full paper text |
sections |
list | Structured sections with title and content |
figures |
list | Figures with id, caption, and content |
references |
list | References with text and doi |
authors |
list | Author information |
Identifier Fields
| Field | Type | Description |
|---|---|---|
corpus_id |
int64 | Semantic Scholar corpus ID |
external_ids |
dict | External IDs (arxiv, doi, mag, acl, pubmed, dblp, etc.) |
Source & Access Fields
| Field | Type | Description |
|---|---|---|
source |
dict | PDF metadata including pdf_urls, pdf_sha, and open_access info |
Usage
from datasets import load_dataset
# stream to avoid downloading 266GB
ds = load_dataset("AlgorithmicResearchGroup/s2orc_arxiv", streaming=True, split="train")
for paper in ds:
print(paper["title"], len(paper["sections"]), "sections")
break
Related Resources
- S2ORC CS Enriched - CS subset with LLM-generated enrichments
- Algorithmic Research Group - Open Source
Citation
@misc{s2orc_arxiv,
title={S2ORC ArXiv},
author={Algorithmic Research Group},
year={2024},
publisher={Hugging Face},
url={https://huggingface.co/datasets/AlgorithmicResearchGroup/s2orc_arxiv}
}
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