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AI Conference & Journal Papers
Searchable metadata and full-text PDF mirrors for papers from top-tier AI venues (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, WACV, ACL, EMNLP, NAACL, IJCAI, AAAI, JMLR, Interspeech) from 2023.
- π
papers.parquet: The complete dataset containing all fields and all venues. - π Per-venue browse views: Easily explore specific subsets by selecting a venue in Subset and a year in Split.
ποΈ Dataset Structure & Storage Strategy
To avoid reaching repository size limits and ensure optimal performance, the project is decoupled into two components:
- Main Registry (This Repository): Contains the complete searchable metadata, individual index files (
papers.parquet), and partitioned per-venue Parquet files (browse/). - PDF Storage Shards: The raw PDF binary files are sharded into separate, venue-specific repositories (
GenAI4ELab/papercli-papers-[venue]).
π οΈ How to Download PDFs
Because the metadata and actual file pointers reside in this main repository, the standard workflow is to query/filter the metadata here first, then programmatically fetch the corresponding PDF binary from its respective shard.
Python Example
Ensure you have the Hugging Face Hub CLI client installed:
pip install huggingface_hub
You can use the following script to look up a paper and pull its mirrored PDF automatically:
from huggingface_hub import hf_hub_download
# Assuming `row` is a dictionary or pandas row obtained from the metadata Parquet
venue_name = row['venue'].lower()
repo_id = f"GenAI4ELab/papercli-papers-{venue_name}"
path = hf_hub_download(
repo_id=repo_id,
filename=row["hf_pdf_path"],
repo_type="dataset",
)
print(f"Downloaded PDF to: {path}")
π Dataset Hub & Venue Directory
Here is the complete navigation map for the main dataset metadata registry and all corresponding sharded PDF storage repositories:
| STT | Venue / Dataset | Repository Link |
|---|---|---|
| 1 | π Main Registry (Metadata) | GenAI4ELab/papercli-papers |
| 2 | π NeurIPS | GenAI4ELab/papercli-papers-neurips |
| 3 | π AAAI | GenAI4ELab/papercli-papers-aaai |
| 4 | π EMNLP | GenAI4ELab/papercli-papers-emnlp |
| 5 | π CVPR | GenAI4ELab/papercli-papers-cvpr |
| 6 | π ICCV | GenAI4ELab/papercli-papers-iccv |
| 7 | π ICML | GenAI4ELab/papercli-papers-icml |
| 8 | π ACL | GenAI4ELab/papercli-papers-acl |
| 9 | π IJCAI | GenAI4ELab/papercli-papers-ijcai |
| 10 | π ECCV | GenAI4ELab/papercli-papers-eccv |
| 11 | π ICLR | GenAI4ELab/papercli-papers-iclr |
| 12 | π NAACL | GenAI4ELab/papercli-papers-naacl |
| 13 | π Interspeech | GenAI4ELab/papercli-papers-interspeech |
| 14 | π WACV | GenAI4ELab/papercli-papers-wacv |
| 15 | π JMLR | GenAI4ELab/papercli-papers-jmlr |
π οΈ Credits & Tools
This dataset was compiled and structured using papercli, an open-source tool designed to index, mirror, and shard academic papers from top-tier AI venues efficiently.
If you find this mirror useful, please consider starring the parent repository and the original papercli project!
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