ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts.

Zexin Wang|Changhua Pei|Yang Liu|Hengyue Jiang|Quan Zhou|Haotian Si|Hang Cui|Jianhui Li|Gaogang Xie|Jingjing Li|Dan Pei


Anthology ID:DBLP:conf/www/WangPLJZSCLXLP26
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:5286-5297
URL:https://doi.org/10.1145/3774904.3792323
DOI:https://doi.org/10.1145/3774904.3792323
DBLP:conf/www/WangPLJZSCLXLP26
BibTeX:
@inproceedings{wang-2026-vits, author = {Zexin Wang and Changhua Pei and Yang Liu and Hengyue Jiang and Quan Zhou and Haotian Si and Hang Cui and Jianhui Li and Gaogang Xie and Jingjing Li and Dan Pei}, editor = {Hakim Hacid and Yoelle Maarek and Francesco Bonchi and Ido Guy and Emine Yilmaz}, title = {{ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts}}, 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 = {5286--5297}, publisher = {ACM}, year = {2026}, url = {https://doi.org/10.1145/3774904.3792323}, doi = {https://doi.org/10.1145/3774904.3792323} }