4 citations · 7 across the 13 of their papers we have counts for
5 papers · 1 filter
CEQuest: Benchmarking Large Language Models for Construction Estimation
Yanzhao Wu, Lufan Wang, Rui Liu
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of general-domain tasks. However, their effectiveness in specialized fields, such as cons…
Retrieval-Augmented Foundation Models for Water Level Prediction in the Everglades
Rahuul Rangaraj, Jimeng Shi, Rajendra Paudel +2
Accurate water level forecasting in the Everglades is essential for flood mitigation, drought management, water resource planning, and biodiversity conservation. While recent time-…
How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades
Rahuul Rangaraj, Jimeng Shi, Azam Shirali +3
The Everglades play a crucial role in flood and drought regulation, water resource planning, and ecosystem management in the surrounding regions. However, traditional physics-based…
NeRF-APT: A New NeRF Framework for Wireless Channel Prediction
Jingzhou Shen, Tianya Zhao, Yanzhao Wu +1
Neural radiance fields (NeRFs) have recently attracted significant attention in the field of wireless channel prediction, primarily due to their capability for high-fidelity recons…
Deep Learning and Foundation Models for Weather Prediction: A Survey
Jimeng Shi, Azam Shirali, Bowen Jin +10
Physics-based numerical models have been the bedrock of atmospheric sciences for decades, offering robust solutions but often at the cost of significant computational resources. De…