1 citations · 1 across the 2 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models
Shilei Cao, Hehai Lin, Jiashun Cheng +9
While recent advances in machine learning have equipped Weather Foundation Models (WFMs) with substantial generalization capabilities across diverse downstream tasks, the escalatin…
cs.LG2026★ 1 cited
TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State
Guowen Li, Xintong Liu, Yang Liu +11
Accurate Subseasonal-to-Seasonal (S2S) forecasting is vital for decision-making in agriculture, energy production, and emergency management. However, it remains a challenging and u…