metadata
viewer: false
dataset: unarxive_2024
title: UnarXive 2024
license: mit
language:
- en
tags:
- scholarly-nlp
- information-retrieval
- citation-network
- scientific-papers
- rag
- qa
size_categories:
- 1M<n<10M
pretty_name: UnarXive 2024
source_datasets:
- arXiv.org
dataset_type: text
multilingual: true
Example Preview
Here is a small excerpt of the dataset format:
📄 preview.jsonl
Dataset Card for UnarXive 2024
UnarXive 2024 is a large-scale, structured dataset of 2.3 million full-text arXiv papers (1991–2024), processed for use in NLP and information retrieval tasks. Each paper is provided in a structured JSONL format.
Features
- 2.28 million structured papers across physics, CS, mathematics, and other fields
- Logical section structure (Introduction, Methods, etc.) for discourse-aware modeling
- Metadata-rich: title, authors, abstract, arXiv ID, categories, license, language, cited_by_count
- In-text citation markers and linked reference entries
- 30M+ citation links with 51.2% resolved to OpenAlex IDs
- Preserved mathematical expressions, figures, and tables with positional spans
- Multilingual content, mostly in English, but includes French, German, Catalan, and more (25+ languages)
Usage
The dataset supports tasks such as citation recommendation, scientific QA, retrieval-augmented generation (RAG), Citation function and polarity classification and paper embedding training.
Pipeline
GitHub: ines-besrour/UnarXive-2024
Dataset licensed under the MIT License.