Cross-Modal Emotion Understanding: A Transformer-GAT Approach for Dialogue Emotion Recognition

arXiv:2609.29556 · cs.AI · Submitted 2026-09-02 · Read on arXiv

cs.AI

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

• Transformer — 38× in this paper · explained in 2 episodes
• F1 Score — 12× in this paper · explained in 3 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Multimodal Fusion — 6× in this paper · explained in 3 episodes
• Frustration — 4× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adaptability — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Affective Computing — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes

Sources

• Multimodal Prompt Learning with Missing Modalities for Sentiment Analysis and Emotion Recognition
• EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa
• LineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks
• InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language Models
• OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• Deep Imbalanced Learning for Multimodal Emotion Recognition in Conversations
• Graph Attention Networks
• Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversation
• TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation
• DialogueLLM: Context and Emotion Knowledge-Tuned Large Language Models for Emotion Recognition in Conversations

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