ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding.
Bingning Wang|Feiyang Lv|Ting Yao|Jin Ma|Yu Luo|Haijin Liang
| Anthology ID: | DBLP:conf/cikm/WangLYMLL22 |
|---|---|
| Volume: | Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022 |
| Year: | 2022 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1996-2006 |
| URL: | https://doi.org/10.1145/3511808.3557258 |
| DOI: | https://doi.org/10.1145/3511808.3557258 |
| DBLP: | conf/cikm/WangLYMLL22 |
| BibTeX: |
@inproceedings{wang-2022-chiqa,
author = {Bingning Wang and
Feiyang Lv and
Ting Yao and
Jin Ma and
Yu Luo and
Haijin Liang},
editor = {Mohammad Al Hasan and
Li Xiong},
title = {{ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding}},
booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}},
pages = {1996--2006},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3511808.3557258},
doi = {https://doi.org/10.1145/3511808.3557258}
}