AdaDebunk: An Efficient and Reliable Deep State Space Model for Adaptive Fake News Early Detection.
Ke Li|Bin Guo|Siyuan Ren|Zhiwen Yu
| Anthology ID: | DBLP:conf/cikm/Li0R022 |
|---|---|
| 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: | 1156-1165 |
| URL: | https://doi.org/10.1145/3511808.3557227 |
| DOI: | https://doi.org/10.1145/3511808.3557227 |
| DBLP: | conf/cikm/Li0R022 |
| BibTeX: |
@inproceedings{li-2022-adadebunk,
author = {Ke Li and
Bin Guo and
Siyuan Ren and
Zhiwen Yu},
editor = {Mohammad Al Hasan and
Li Xiong},
title = {{AdaDebunk: An Efficient and Reliable Deep State Space Model for Adaptive Fake News Early Detection}},
booktitle = {{Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022}},
pages = {1156--1165},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3511808.3557227},
doi = {https://doi.org/10.1145/3511808.3557227}
}