4 papers
Enhancing Visual Question Answering with Multimodal LLMs via Chain-of-Question Guided Retrieval-Augmented Generation
Quanxing Xu, Ling Zhou, Xian Zhong +3
With advances in multimodal research and deep learning, Multimodal Large Language Models (MLLMs) have emerged as a powerful paradigm for a wide range of multimodal tasks. As a core…
PC-MNet: Dual-Level Congruity Modeling for Multimodal Sarcasm Detection via Polarity-Modulated Attention
Maoheng Li, Ling Zhou, Xiaohua Huang +3
Multimodal sarcasm detection, which aims to precisely identify pragmatic incongruities between literal text and nonverbal cues, has gained substantial attention in multimodal under…
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…
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…