Author

Ying Sha

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Jul 2026

Semantic-Aligned Structural Abstraction for Multimodal Sentiment Analysis

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, Junkai Li, Tongguan Wang et al. · arXiv.org · 0 citations