metadata
dataset_info:
features:
- name: date
dtype: timestamp[s]
- name: paper_id
dtype: string
- name: title
dtype: string
- name: authors
dtype: string
- name: num_authors
dtype: int64
splits:
- name: train
num_bytes: 824984
num_examples: 5117
download_size: 509022
dataset_size: 824984
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
HF-Daily-Papers
Overview
The HF-Daily-Papers dataset is a curated collection of academic papers gathered from various sources up until January 10, 2025. This dataset is designed to support researchers, data scientists, and AI enthusiasts working with Natural Language Processing (NLP), Machine Learning (ML), and scientific literature analysis.
Contents
- PDF Files: The dataset consists of research papers in PDF format, organized by date of collection.
- Metadata: Each paper is accompanied by relevant metadata, including title, authors, and publication date where available.
Format
The dataset is available as a zip file containing all the research papers in their original format.
How to Access
You can download the dataset directly from Hugging Face using:
huggingface-cli download Nayana-cognitivelab/HF-Daily-Papers
Alternatively, access it via the Hugging Face Datasets library:
from datasets import load_dataset
dataset = load_dataset("Nayana-cognitivelab/HF-Daily-Papers")
Citation
If you use this dataset in your research or projects, please cite it as follows:
@dataset{hf_daily_papers_2025,
title = {HF-Daily-Papers},
author = {Nayana-CognitiveLab},
year = {2025},
note = {Dataset available on Hugging Face Datasets}
}
Last Updated: January 10, 2025