3 citations · 5 across the 4 of their papers we have counts for
4 papers
VeritasFi: An Adaptable, Multi-tiered RAG Framework for Multi-modal Financial Question Answering
Zhenghan Tai, Hanwei Wu, Qingchen Hu +24
Retrieval-Augmented Generation (RAG) is becoming increasingly essential for Question Answering (QA) in the financial sector, where accurate and contextually grounded insights from…
Interpretable Load Forecasting via Representation Learning of Geo-distributed Meteorological Factors
Yangze Zhou, Guoxin Lin, Gonghao Zhang +1
Meteorological factors (MF) are crucial in day-ahead load forecasting as they significantly influence the electricity consumption behaviors of consumers. Numerous studies have inco…
Improving the Accuracy and Interpretability of Neural Networks for Wind Power Forecasting
Wenlong Liao, Fernando Porte-Agel, Jiannong Fang +3
Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their f…
An Explainable Framework for Machine learning-Based Reactive Power Optimization of Distribution Network
Wenlong Liao, Benjamin Schäfer, Dalin Qin +3
To reduce the heavy computational burden of reactive power optimization of distribution networks, machine learning models are receiving increasing attention. However, most machine…