Tabular Foundation Models are Strong Graph Anomaly Detectors.
Yunhui Liu|Tieke He|Yongchao Liu|Can Yi|Hong Jin|Chuntao Hong
| Anthology ID: | DBLP:conf/www/LiuHLYJH26 |
|---|---|
| Volume: | Proceedings of the ACM Web Conference 2026, WWW 2026, Dubai, United Arab Emirates, originally scheduled for April 13-17, 2026, rescheduled for June 29 - July 3, 2026. |
| Year: | 2026 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 8785-8788 |
| URL: | https://doi.org/10.1145/3774904.3792965 |
| DOI: | https://doi.org/10.1145/3774904.3792965 |
| DBLP: | conf/www/LiuHLYJH26 |
| BibTeX: |
@inproceedings{liu-2026-tabular,
author = {Yunhui Liu and
Tieke He and
Yongchao Liu and
Can Yi and
Hong Jin and
Chuntao Hong},
editor = {Hakim Hacid and
Yoelle Maarek and
Francesco Bonchi and
Ido Guy and
Emine Yilmaz},
title = {{Tabular Foundation Models are Strong Graph Anomaly Detectors}},
booktitle = {{Proceedings of the ACM Web Conference 2026, WWW 2026, Dubai, United Arab Emirates, originally scheduled for April 13-17, 2026, rescheduled for June 29 - July 3, 2026}},
pages = {8785--8788},
publisher = {ACM},
year = {2026},
url = {https://doi.org/10.1145/3774904.3792965},
doi = {https://doi.org/10.1145/3774904.3792965}
}