Emotion Recognition In Conversation On

Metriken

Accuracy

Weighted-F1

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

			Paper Title
SDT	73.95	74.08	A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversations
GS-MCC	73.8	73.9	Revisiting Multimodal Emotion Recognition in Conversation from the Perspective of Graph Spectrum
Mamba-like Model	73.1	73.3	Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion
GraphSmile	72.77	72.81	Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition
SpeechCueLLM	-	72.596	Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances
MPT-HCL	72.83	72.51	Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation
CKERC	-	72.40	LaERC-S: Improving LLM-based Emotion Recognition in Conversation with Speaker Characteristics
EmoCaps	-	71.77	EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition
DF-ERC	71.84	71.75	Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition
InstructERC	71.68	71.39	InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language Models
BiosERC	-	71.19	BiosERC: Integrating Biography Speakers Supported by LLMs for ERC Tasks
SAMGN	-	71.11	Structure-Aware Transformer for Graph Representation Learning
CFN-ESA	70.78	71.04	CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion Recognition
ELR-GNN	70.6	70.9	Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations
UniMSE	70.56	70.66	UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognition
TelME	-	70.48	TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation
EACL	-	70.41	Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversation
GA2MIF	69.75	70.00	GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion Detection
M2FNet	69.69	69.86	M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversation
SPCL-CL-ERC	-	69.74	Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation

0 of 60 row(s) selected.

Command Palette

Emotion Recognition In Conversation On

Metriken

Ergebnisse