1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2025
AtmosSci-Bench: Evaluating the Recent Advance of Large Language Model for Atmospheric Science
Chenyue Li, Wen Deng, Mengqian Lu +1
The rapid advancements in large language models (LLMs), particularly in their reasoning capabilities, hold transformative potential for addressing complex challenges and boosting s…
cs.LG2024★ 1 cited
On the Opportunities of (Re)-Exploring Atmospheric Science by Foundation Models: A Case Study
Lujia Zhang, Hanzhe Cui, Yurong Song +3
Most state-of-the-art AI applications in atmospheric science are based on classic deep learning approaches. However, such approaches cannot automatically integrate multiple complic…