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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 51–100 of 202 papers

TitleStatusHype
MSE-Adapter: A Lightweight Plugin Endowing LLMs with the Capability to Perform Multimodal Sentiment Analysis and Emotion RecognitionCode1
The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and StressCode1
Exploiting BERT For Multimodal Target Sentiment Classification Through Input Space TranslationCode1
MuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and WorkshopCode1
Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR ErrorsCode1
CTFN: Hierarchical Learning for Multimodal Sentiment Analysis Using Coupled-Translation Fusion NetworkCode1
Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment AnalysisCode1
Cooperative Sentiment Agents for Multimodal Sentiment AnalysisCode1
EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion UnderstandingCode1
Multi-Modality Collaborative Learning for Sentiment AnalysisCode1
Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal RepresentationsCode1
Cross-Modal BERT for Text-Audio Sentiment AnalysisCode1
Generalizable Multi-linear Attention Network—0
Correlation-Decoupled Knowledge Distillation for Multimodal Sentiment Analysis with Incomplete Modalities—0
Gated Mechanism for Attention Based Multimodal Sentiment Analysis—0
CorMulT: A Semi-supervised Modality Correlation-aware Multimodal Transformer for Sentiment Analysis—0
Findings of the Shared Task on Multimodal Sentiment Analysis and Troll Meme Classification in Dravidian Languages—0
Exploring Multimodal Sentiment Analysis via CBAM Attention and Double-layer BiLSTM Architecture—0
Exploring Large Language Models for Multimodal Sentiment Analysis: Challenges, Benchmarks, and Future Directions—0
A Text-Centered Shared-Private Framework via Cross-Modal Prediction for Multimodal Sentiment Analysis—0
A Multimodal Sentiment Dataset for Video Recommendation—0
Exploiting Diverse Feature for Multimodal Sentiment Analysis—0
Contextual Augmented Global Contrast for Multimodal Intent Recognition—0
Explainable Multimodal Sentiment Analysis on Bengali Memes—0
A Self-Adjusting Fusion Representation Learning Model for Unaligned Text-Audio Sequences—0
A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis—0
Enriching Multimodal Sentiment Analysis through Textual Emotional Descriptions of Visual-Audio Content—0
Modeling Intra- and Inter-Modal Relations: Hierarchical Graph Contrastive Learning for Multimodal Sentiment Analysis—0
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis—0
Modality Influence in Multimodal Machine Learning—0
Missing Modality meets Meta Sampling (M3S): An Efficient Universal Approach for Multimodal Sentiment Analysis with Missing Modality—0
Emoji Driven Crypto Assets Market Reactions—0
CMSBERT-CLR: Context-driven Modality Shifting BERT with Contrastive Learning for linguistic, visual, acoustic Representations—0
AMOA: Global Acoustic Feature Enhanced Modal-Order-Aware Network for Multimodal Sentiment Analysis—0
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph—0
Dynamic Multimodal Sentiment Analysis: Leveraging Cross-Modal Attention for Enabled Classification—0
Adversarial Multimodal Domain Transfer for Video-Level Sentiment Analysis—0
DravidianMultiModality: A Dataset for Multi-modal Sentiment Analysis in Tamil and Malayalam—0
MART: Masked Affective RepresenTation Learning via Masked Temporal Distribution Distillation—0
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability—0
DNN Multimodal Fusion Techniques for Predicting Video Sentiment—0
Multimodal Contrastive Learning via Uni-Modal Coding and Cross-Modal Prediction for Multimodal Sentiment Analysis—0
Meta-Learn Unimodal Signals with Weak Supervision for Multimodal Sentiment Analysis—0
M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis—0
Lightweight Models for Multimodal Sequential Data—0
An AutoML-based Approach to Multimodal Image Sentiment Analysis—0
Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis—0
Modality-Invariant Bidirectional Temporal Representation Distillation Network for Missing Multimodal Sentiment Analysis—0
Learning Robust Joint Representations for Multimodal Sentiment Analysis—0
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis—0
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