Do-GOOD: Towards Distribution Shift Evaluation for Pre-Trained Visual Document Understanding Models.
Jiabang He|Yi Hu|Lei Wang|Xing Xu|Ning Liu|Hui Liu|Heng Tao Shen
| Anthology ID: | DBLP:conf/sigir/HeHWXLLS23 |
|---|---|
| Volume: | Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023 |
| Year: | 2023 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 569-579 |
| URL: | https://doi.org/10.1145/3539618.3591670 |
| DOI: | https://doi.org/10.1145/3539618.3591670 |
| DBLP: | conf/sigir/HeHWXLLS23 |
| BibTeX: |
@inproceedings{he-2023-dogood,
author = {Jiabang He and
Yi Hu and
Lei Wang and
Xing Xu and
Ning Liu and
Hui Liu and
Heng Tao Shen},
editor = {Hsin-Hsi Chen and
Wei-Jou (Edward) Duh and
Hen-Hsen Huang and
Makoto P. Kato and
Josiane Mothe and
Barbara Poblete},
title = {{Do-GOOD: Towards Distribution Shift Evaluation for Pre-Trained Visual Document Understanding Models}},
booktitle = {{Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023}},
pages = {569--579},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3539618.3591670},
doi = {https://doi.org/10.1145/3539618.3591670}
}