综述

Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges
paper link: https://dl.acm.org/doi/abs/10.1145/3586075

2023

1. Few-shot Multimodal Sentiment Analysis Based on Multimodal Probabilistic Fusion Prompts
   paper link: https://dl.acm.org/doi/pdf/10.1145/3581783.3612181
   code link: https://github.com/YangXiaocui1215/MultiPoint
2. Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt
   paper link: https://arxiv.org/abs/2305.10169
   code link: https://github.com/yangxiaocui1215/gmp
3. Syntax-aware Hybrid prompt model for Few-shot multi-modal sentiment analysis
   paper link: https://arxiv.org/abs/2306.01312

2022

1. Few-Shot Multi-Modal Sentiment Analysis with Prompt-Based Vision-Aware Language Modeling
   paper link: https://ieeexplore.ieee.org/abstract/document/9859654
   code link: https://github.com/yynj98/PVLM
2. Unified Multi-modal Pre-training for Few-shot Sentiment Analysis with Prompt-based Learning
   paper link: https://dl.acm.org/doi/abs/10.1145/3503161.3548306
   code link: https://github.com/yynj98/UP-MPF
3. CLMLF:A Contrastive Learning and Multi-Layer Fusion Method for Multimodal Sentiment Detection
   paper link: https://arxiv.org/abs/2204.05515
   code link: https://github.com/link-li/clmlf

2021

1. Multimodal Few-Shot Learning with Frozen Language Models
   paper link: https://arxiv.org/abs/2106.13884
   code link: https://github.com/ilkerkesen/frozen