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20242026
most citedShort-Term Electricity-Load Forecasting by Deep Learning: A Comprehensive Survey

91 citations · 92 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

ASafe: Counterfactual Evidence-Aligned Adaptive Agent Collaboration for Safe and Effective Visual Question Answering

Quanxing Xu, Ling Zhou, Xian Zhong +4

Visual Question Answering (VQA) with Multimodal Large Language Models (MLLMs) requires not only producing safe and effective responses, but also grounding safety decisions in the m…

cs.LG2026

Short-term electricity load forecasting with multi-frequency reconstruction diffusion

Qi Dong, Rubing Huang, Ling Zhou +3

Diffusion models have emerged as a powerful method in various applications. However, their application to Short-Term Electricity Load Forecasting (STELF) -- a typical scenario in e…

cs.CV2025

OAD-Promoter: Enhancing Zero-shot VQA using Large Language Models with Object Attribute Description

Quanxing Xu, Ling Zhou, Feifei Zhang +2

Large Language Models (LLMs) have become a crucial tool in Visual Question Answering (VQA) for handling knowledge-intensive questions in few-shot or zero-shot scenarios. However, t…

q-bio.QM2024★ 1 cited

Ribonucleic-Acid Protein Interaction Prediction Based on Deep Learning: A Comprehensive Survey

Danyu Li, Rubing Huang, Chenhui Cui +4

The interaction between Ribonucleic Acids (RNAs) and proteins, also called RNA Protein Interaction (RPI), governs biological processes, including gene regulation and disease pathog…

cs.LG2024★ 91 cited

Short-Term Electricity-Load Forecasting by Deep Learning: A Comprehensive Survey

Qi Dong, Rubing Huang, Chenhui Cui +4

Short-Term Electricity-Load Forecasting (STELF) refers to the prediction of the immediate demand (in the next few hours to several days) for the power system. Various external fact…