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cs.LG2025
Efficient Prompting for Continual Adaptation to Missing Modalities
Zirun Guo, Shulei Wang, Wang Lin +3
Missing modality issues are common in real-world applications, arising from factors such as equipment failures and privacy concerns. When fine-tuning pre-trained models on downstre…
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…