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 multimodal 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 Pretraining 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

原文地址:https://blog.csdn.net/weixin_41845840/article/details/134722371

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任

如若转载,请注明出处:http://www.7code.cn/show_22380.html

如若内容造成侵权/违法违规/事实不符,请联系代码007邮箱suwngjj01@126.com进行投诉反馈,一经查实,立即删除

发表回复

您的邮箱地址不会被公开。 必填项已用 * 标注