3 papers
cs.LG2024
A Wander Through the Multimodal Landscape: Efficient Transfer Learning via Low-rank Sequence Multimodal Adapter
Zirun Guo, Xize Cheng, Yangyang Wu +1
Efficient transfer learning methods such as adapter-based methods have shown great success in unimodal models and vision-language models. However, existing methods have two main ch…
cs.LG2024
Bridging the Gap for Test-Time Multimodal Sentiment Analysis
Zirun Guo, Tao Jin, Wenlong Xu +2
Multimodal sentiment analysis (MSA) is an emerging research topic that aims to understand and recognize human sentiment or emotions through multiple modalities. However, in real-wo…
cs.LG2024
SEGAN: semi-supervised learning approach for missing data imputation
Xiaohua Pan, Weifeng Wu, Peiran Liu +6
In many practical real-world applications, data missing is a very common phenomenon, making the development of data-driven artificial intelligence theory and technology increasingl…