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Multimodal Sentiment Analysis

Multimodal sentiment analysis is the task of performing sentiment analysis with multiple data sources - e.g. a camera feed of someone's face and their recorded speech.

( Image credit: ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection )

Papers

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Showing 81–90 of 202 papers

TitleStatusHype
Exploring Large Language Models for Multimodal Sentiment Analysis: Challenges, Benchmarks, and Future Directions—0
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning—0
Learning in Order! A Sequential Strategy to Learn Invariant Features for Multimodal Sentiment Analysis—0
Meta-Learn Unimodal Signals with Weak Supervision for Multimodal Sentiment Analysis—0
GSIFN: A Graph-Structured and Interlaced-Masked Multimodal Transformer-based Fusion Network for Multimodal Sentiment AnalysisCode0
CorMulT: A Semi-supervised Modality Correlation-aware Multimodal Transformer for Sentiment Analysis—0
Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey—0
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor RecognitionCode0
PTA: Enhancing Multimodal Sentiment Analysis through Pipelined Prediction and Translation-based Alignment—0
RNG: Reducing Multi-level Noise and Multi-grained Semantic Gap for Joint Multimodal Aspect-Sentiment Analysis—0
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