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算力平台

Emotion Recognition In Conversation On 7

评估指标

Accuracy
Weighted F1

评测结果

各个模型在此基准测试上的表现结果

Paper Title
GraphSmile86.5386.52Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition
Joyful-85.70Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion Recognition
COGMEN-84.50COGMEN: COntextualized GNN based Multimodal Emotion recognitioN
M3Net83.6783.57Multivariate, Multi-Frequency and Multimodal: Rethinking Graph Neural Networks for Emotion Recognition in Conversation
DialogueCRN81.3481.28DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations
MM-DFN80.9180.83MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in Conversations
SACL-LSTM80.7080.74Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations
MMGCN79.7579.72MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversation
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Emotion Recognition In Conversation On 7 | SOTA | HyperAI超神经