ConsMSA: Semantic Distribution Consistency Learning for Multimodal Sentiment Analysis

Overview

arXiv:2610.31731v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) aims to predict human sentiments by integrating signals from different modalities such as text, video, and audio. However, raw multimodal sequences often suffer from semantic inconsistency--exhibiting redundancy or conflicts within and across modalities--which hinders robust understanding and increases computational cost. To this end, we introduce ConsMSA, which explicitly formalizes semantic distribution consist

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