Dataset Viewer
Auto-converted to Parquet Duplicate
The dataset viewer is not available for this split.
Parquet error: Scan size limit exceeded: attempted to read 804737472 bytes, limit is 300000000 bytes Make sure that 1. the Parquet files contain a page index to enable random access without loading entire row groups2. otherwise use smaller row-group sizes when serializing the Parquet files
Error code:   TooBigContentError

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Scientific Papers - Raw Full Text

~57 million scientific papers with full text, extracted from multiple large-scale academic paper collections. This dataset provides raw full text suitable for pre-training, fine-tuning, or building search indices over scientific literature.

Subsets

Subset Papers Size Source
papers-2 ~18.5M ~358 GB S2ORC papers collection (untitled subset)
papers-3 ~27.4M ~198 GB S2ORC scientific-papers collection
pes2o ~8.2M ~106 GB Pes2oX-fulltext (Semantic Scholar, Apache 2.0)
corex ~2.9M ~25 GB CORE repository (core.ac.uk, Apache 2.0)
Total ~57M ~687 GB

Schema (9 columns)

Column Type Description
paper_id string Unique identifier (source-specific)
title string Paper title (when available)
authors string Author names (semicolon-separated)
year string Publication year (when available)
venue string Publication venue (when available)
doi string DOI (when available)
abstract string Paper abstract (when available)
raw_fulltext string Complete paper text
text_length int64 Character count of full text

Usage

from datasets import load_dataset

# Load a specific subset
ds = load_dataset("scientifi-papers/scientific-papers", "corex")

# Load papers-3 (largest)
ds = load_dataset("scientifi-papers/scientific-papers", "papers-3")

# Access full text
paper = ds['train'][0]
print(f"Title: {paper['title']}")
print(f"Text length: {paper['text_length']} chars")
print(paper['raw_fulltext'][:500])

Sources

  • papers-2 / papers-3: Extracted from the Semantic Scholar Open Research Corpus (S2ORC) via GROBID PDF parsing
  • pes2o: Allen AI's Pes2oX-fulltext dataset (cleaned S2ORC full text)
  • corex: CORE repository (core.ac.uk) - 2018 full-text dump of open-access research papers

License

CC-BY-4.0

Downloads last month
146