In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks.

Shangqing Xu|Harshavardhan Kamarthi|Haoxin Liu|B. Aditya Prakash


Anthology ID:DBLP:conf/cikm/XuK0P25
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:5386-5390
URL:https://doi.org/10.1145/3746252.3760801
DOI:https://doi.org/10.1145/3746252.3760801
DBLP:conf/cikm/XuK0P25
BibTeX:
@inproceedings{xu-2025-incontext, author = {Shangqing Xu and Harshavardhan Kamarthi and Haoxin Liu and B. Aditya Prakash}, 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 = {{In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {5386--5390}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3760801}, doi = {https://doi.org/10.1145/3746252.3760801} }