metadata
license: cc-by-4.0
pretty_name: AI Conference & Journal Papers
configs:
- config_name: aaai
data_files:
- split: '2026'
path: browse/aaai/2026.parquet
- split: '2025'
path: browse/aaai/2025.parquet
- split: '2024'
path: browse/aaai/2024.parquet
- split: '2023'
path: browse/aaai/2023.parquet
- config_name: acl
data_files:
- split: '2025'
path: browse/acl/2025.parquet
- split: '2024'
path: browse/acl/2024.parquet
- split: '2023'
path: browse/acl/2023.parquet
- config_name: cvpr
data_files:
- split: '2026'
path: browse/cvpr/2026.parquet
- split: '2025'
path: browse/cvpr/2025.parquet
- split: '2024'
path: browse/cvpr/2024.parquet
- split: '2023'
path: browse/cvpr/2023.parquet
- config_name: eccv
data_files:
- split: '2024'
path: browse/eccv/2024.parquet
- split: '2022'
path: browse/eccv/2022.parquet
- split: '2020'
path: browse/eccv/2020.parquet
- config_name: emnlp
data_files:
- split: '2025'
path: browse/emnlp/2025.parquet
- split: '2024'
path: browse/emnlp/2024.parquet
- split: '2023'
path: browse/emnlp/2023.parquet
- config_name: iccv
data_files:
- split: '2025'
path: browse/iccv/2025.parquet
- split: '2023'
path: browse/iccv/2023.parquet
- config_name: iclr
data_files:
- split: '2026'
path: browse/iclr/2026.parquet
- split: '2025'
path: browse/iclr/2025.parquet
- split: '2024'
path: browse/iclr/2024.parquet
- split: '2023'
path: browse/iclr/2023.parquet
- config_name: icml
data_files:
- split: '2025'
path: browse/icml/2025.parquet
- split: '2024'
path: browse/icml/2024.parquet
- split: '2023'
path: browse/icml/2023.parquet
- config_name: ijcai
data_files:
- split: '2025'
path: browse/ijcai/2025.parquet
- split: '2024'
path: browse/ijcai/2024.parquet
- split: '2023'
path: browse/ijcai/2023.parquet
- config_name: interspeech
data_files:
- split: '2025'
path: browse/interspeech/2025.parquet
- split: '2024'
path: browse/interspeech/2024.parquet
- split: '2023'
path: browse/interspeech/2023.parquet
- config_name: jmlr
data_files:
- split: '2025'
path: browse/jmlr/2025.parquet
- split: '2024'
path: browse/jmlr/2024.parquet
- split: '2023'
path: browse/jmlr/2023.parquet
- split: '2022'
path: browse/jmlr/2022.parquet
- config_name: naacl
data_files:
- split: '2025'
path: browse/naacl/2025.parquet
- split: '2024'
path: browse/naacl/2024.parquet
- config_name: neurips
data_files:
- split: '2025'
path: browse/neurips/2025.parquet
- split: '2024'
path: browse/neurips/2024.parquet
- split: '2023'
path: browse/neurips/2023.parquet
- config_name: wacv
data_files:
- split: '2026'
path: browse/wacv/2026.parquet
- split: '2025'
path: browse/wacv/2025.parquet
- split: '2024'
path: browse/wacv/2024.parquet
- split: '2023'
path: browse/wacv/2023.parquet
AI Conference & Journal Papers
Searchable metadata for papers from top AI venues (NeurIPS, ICML, ICLR, CVPR, ICCV, WACV, ACL, EMNLP, NAACL).
papers.parquet: the full dataset (all fields, all venues).- Per-venue browse views: pick a venue in Subset, a year in Split.
Dataset Structure
ClosedUni/papercli-papers(main entrypoint): Contains the full index metadata parquet (papers.parquet) and the per-venue browse parquet views (browse/).ClosedUni/papercli-papers-[venue]: Contains the sharded PDF files of that specific venue (no metadata parquet).
PDF Storage
PDF files are sharded across separate datasets by venue to keep repository sizes optimal:
ClosedUni/papercli-papers-[venue](e.g.ClosedUni/papercli-papers-cvprfor CVPR PDFs)
To download a mirrored PDF:
from huggingface_hub import hf_hub_download
repo_id = f"ClosedUni/papercli-papers-{row['venue'].lower()}"
path = hf_hub_download(
repo_id=repo_id,
filename=row["hf_pdf_path"],
repo_type="dataset",
)
Built with papercli.