This repository provides QASA dataset of the following paper: QASA: Advanced Question Answering on Scientific Articles
- Authors: {Yoonjoo Lee*, Kyungjae Lee*}, Sunghyun Park, Dasol Hwang, Jaehyeon Kim, Hong-in Lee, Moontae Lee (* Equal Contribution)
- ICML 2023
- The original benchmark (1798 examples mentioned in our paper) can be found at
data/v0/testset_1798_v0.json - After paper submission, we found noisy cases that are unanswerable in a given paper.
- Therefore, we classified the unanswerable cases, and release a separated version (v1): answerable (
data/testset_answerable_1554_v1.json) & unanswerable (data/testset_unanswerable_244_v1.json). - Released a minor updated version (v1.1) of QASA containing the URL to access the full text. (
data/testset_answerable_1554_v1.1.json,data/testset_answerable_1554_v1.1.json) - If you want to access the full body text of the paper, you can use
src/get_paragraphs.py.
QASA
MIT License
Copyright (c) 2023 LG AI Research
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SOFTWARE.
@inproceedings{lee2023qasa,
title={QASA: Advanced Question Answering on Scientific Articles},
author={Lee, Yoonjoo and Lee, Kyungjae and Park, Sunghyun and Hwang, Dasol and Kim, Jaehyeon and Lee, Hong-in and Lee, Moontae},
booktitle={Proceedings of the 40th International Conference on Machine Learning},
year={2023}
}
If you have any questions, please send an email to: Moontae Lee (moontae.lee@lgresearch.ai)
