FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection.

Yunfeng Zhao|Yixin Liu|Shiyuan Li|Qingfeng Chen|Yu Zheng|Shirui Pan


Anthology ID:DBLP:conf/cikm/Zhao0LC0P25
Volume:Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025
Year:2025
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:4379-4389
URL:https://doi.org/10.1145/3746252.3761125
DOI:https://doi.org/10.1145/3746252.3761125
DBLP:conf/cikm/Zhao0LC0P25
BibTeX:
@inproceedings{zhao-2025-freegad, author = {Yunfeng Zhao and Yixin Liu and Shiyuan Li and Qingfeng Chen and Yu Zheng and Shirui Pan}, editor = {Meeyoung Cha and Carl Yang and Senjuti Basu Roy and Chanyoung Park and Zhenhui Jessie Li and Noseong Park and Carl Yang and Senjuti Basu Roy and Zhenhui Jessie Li and Jaap Kamps and Kijung Shin and Bryan Hooi and Lifang He}, title = {{FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {4379--4389}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3761125}, doi = {https://doi.org/10.1145/3746252.3761125} }