Datasets:
pdf
pdf | label
class label 18
classes |
|---|---|
0acl2016
|
|
1acl2019
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
|
2acl2023
|
AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation
This repository contains the metadata, processed_data and papers for the AirQA dataset introduced in our paper AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation accepted to ICLR 2026. Detailed instructions for using the dataset will soon be publicly available in our official repository.
AirQA is a human-annotated multi-modal multitask Artificial Intelligence Research Question Answering dataset, which encompasses 1,246 examples and 13,956 papers, aiming at evaluating an agentβs research capabilities in realistic scenarios. It is the first dataset that encompasses multiple question types, also the first to bring function-based evaluation into QA domain, enabling convenient and systematic assessment of research capabilities.
π Folder Structure
metadata/
|ββ a0008a3c-743d-5589-bea2-0f4aad710e50.json
βββ ... # more metadata dicts
papers/
|ββ acl2023/
| |ββ 001ab93b-7665-5d56-a28e-eac95d2a9d7e.pdf
| βββ ... # more .pdf published in ACL 2023
βββ ... # other sub-folders of paper collections
processed_data/
|ββ a0008a3c-743d-5589-bea2-0f4aad710e50.json # cached data for PDF parsing
βββ ... # more cached data for PDFs
Due to Hugging Face's limit on the number of files in a single folder, we packaged metadata and processed_data into archives.
π Dataset Statistics
Our dataset encompasses papers from 34 volumes, spanning 7 conferences over 16 years. The detailed distribution is summarized below.
ππ» Click to view the paper distribution of dataset
| Folder | Conference | Year | Collected |
|---|---|---|---|
| iclr2024 | ICLR | 2024 | 3301 |
| iclr2023 | ICLR | 2023 | 31 |
| iclr2020 | ICLR | 2020 | 1 |
| neurips2024 | NeurIPS | 2024 | 6857 |
| neurips2023 | NeurIPS | 2023 | 73 |
| nips2006 | NeurIPS | 2006 | 1 |
| acl2024 | ACL | 2024 | 161 |
| acl2023 | ACL | 2023 | 3083 |
| acl2019 | ACL | 2019 | 1 |
| acl2019 | ACL | 2016 | 1 |
| emnlp2024 | EMNLP | 2024 | 55 |
| emnlp2023 | EMNLP | 2023 | 52 |
| emnlp2021 | EMNLP | 2021 | 2 |
| emnlp2013 | EMNLP | 2013 | 1 |
| icassp2024 | ICASSP | 2024 | 18 |
| icassp2023 | ICASSP | 2023 | 12 |
| eacl2024 | EACL | 2024 | 1 |
| ijcnlp2023 | IJCNLP | 2023 | 1 |
| arxiv2025 | arXiv | 2025 | 12 |
| arxiv2024 | arXiv | 2024 | 53 |
| arxiv2023 | arXiv | 2023 | 61 |
| arxiv2022 | arXiv | 2022 | 61 |
| arxiv2021 | arXiv | 2021 | 43 |
| arxiv2020 | arXiv | 2020 | 25 |
| arxiv2019 | arXiv | 2019 | 20 |
| arxiv2018 | arXiv | 2018 | 11 |
| arxiv2017 | arXiv | 2017 | 6 |
| arxiv2016 | arXiv | 2016 | 4 |
| arxiv2015 | arXiv | 2015 | 1 |
| arxiv2014 | arXiv | 2014 | 1 |
| arxiv2013 | arXiv | 2013 | 1 |
| arxiv2012 | arXiv | 2012 | 1 |
| arxiv2011 | arXiv | 2011 | 1 |
| uncategorized | - | - | 3 |
| Total | - | - | 13956 |
βπ» Citation
If you find this dataset useful, please cite our work:
@misc{huang2025airqacomprehensiveqadataset,
title={AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation},
author={Tiancheng Huang and Ruisheng Cao and Yuxin Zhang and Zhangyi Kang and Zijian Wang and Chenrun Wang and Yijie Luo and Hang Zheng and Lirong Qian and Lu Chen and Kai Yu},
year={2025},
eprint={2509.16952},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2509.16952},
}
- Downloads last month
- 25