A prototype-as-prompt framework that maps audio–visual representations into a fixed set of multimodal sentiment prototypes that are used as soft prompts to guide the LLM in performing MSA and introduces a sentiment-aware prototype learning that explicitly binds multimodal prototypes with sentiment semantics.
MGSI first encodes audio and visual streams at short-, medium-, and long-range temporal scales, preserving both local variations and global affective trends, and applies polarity- and intensity-aware enhancement to better handle ambiguous and near-neutral samples.
Shanshan Lin, Yuesheng Wu, Chao Chen et al.· 0 citations
SentiLLM is proposed, a unified framework that leverages Semantic-Aligned Structural Abstraction to distill continuous raw signals into compact, semantically meaningful tokens and significantly improves discriminative performance with only a small number of trainable parameters.
Wei Chen, Jun-Kai Li, Tongguan Wang et al.· arXiv.org· 0 citations
This work proposes LLM-Augmented Prompt Learning for Multimodal Sentiment Analysis with Reward Adaptation (LAPM-RA), a unified framework integrating LLM-based sentiment-aware augmentation, reward-guided prompt selection, and context-aware multimodal fusion.
In multimodal sentiment analysis, textual, acoustic, and visual modalities often contain redundant and noisy information. Such information increases model complexity and weakens core sentiment representations, degrading accuracy and robustness. To address this issue, we propose CLIBN, a multimodal sentiment recognition...
Xu Meng, Yi Zhang, Yang Li· 2026 8th International Confe...· 0 citations
A multimodal solution that integrates audio and text information via cross-modal transformers, where text transcripts are automatically generated via an automatic speech recognition (ASR) tool and multiple text modalities are created via a cascaded architecture comprising cross-modal transformer blocks that integrate m...
Andrei-George Durdun, V. Constantinescu, R. Ionescu· 0 citations
The framework first introduces learnable sentiment prototypes as semantic anchors to provide explicit sentiment-discriminative guidance for feature completion, and a gradient decoupling strategy is designed to separate the optimization paths of unimodal and multimodal objectives, preventing fusion gradients from interf...
Shan Tao, Haipeng Chen, Yu Liu et al.· Multimedia Systems· 0 citations
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