STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis.

Wenbin Li|Di Yao|Ruibo Zhao|Wenjie Chen|Zijie Xu|Chengxue Luo|Chang Gong|Quanliang Jing|Haining Tan|Jingping Bi


Anthology ID:DBLP:conf/www/00120ZC0L0JTB25
Volume:Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025
Year:2025
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:749-752
URL:https://doi.org/10.1145/3701716.3715293
DOI:https://doi.org/10.1145/3701716.3715293
DBLP:conf/www/00120ZC0L0JTB25
BibTeX:
@inproceedings{li-2025-stbench, author = {Wenbin Li and Di Yao and Ruibo Zhao and Wenjie Chen and Zijie Xu and Chengxue Luo and Chang Gong and Quanliang Jing and Haining Tan and Jingping Bi}, editor = {Guodong Long and Michale Blumestein and Yi Chang and Liane Lewin-Eytan and Zi Huang and Elad Yom-Tov}, title = {{STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis}}, booktitle = {{Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025}}, pages = {749--752}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3701716.3715293}, doi = {https://doi.org/10.1145/3701716.3715293} }