| TODKAT |
- Weighted-F1
- 65.47
|
Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection
2021-06-02 |
연결 없음 |
| TUCORE-GCN_RoBERTa |
- Weighted-F1
- 65.36
|
Graph Based Network with Contextualized Representations of Turns in Dialogue
2021-09-09 |
코드 1 |
| COSMIC |
- Weighted-F1
- 65.21
|
COSMIC: COmmonSense knowledge for eMotion Identification in Conversations
2020-10-06 |
코드 1 |
| SKAIG-ERC |
- Weighted-F1
- 65.18
|
Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological Knowledge
논문 날짜 미기재 |
코드 1 |
| EmotionFlow-base |
- Weighted-F1
- 65.05
|
EmotionFlow: Capture the Dialogue Level Emotion Transitions
2022-05-07 |
코드 1 |
| MPT-HCL |
- Weighted-F1
- 65.02
- Accuracy
- 65.86
|
Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation
2023-10-04 |
연결 없음 |
| CoG-BART |
- Weighted-F1
- 64.81
|
Contrast and Generation Make BART a Good Dialogue Emotion Recognizer
2021-12-21 |
코드 1 |
| AccumWR |
- Weighted-F1
- 64.58
|
Accumulating Word Representations in Multi-level Context Integration for ERC Task
2023-11-06 |
코드 1 |
| ERMC-DisGCN |
- Weighted-F1
- 64.22
|
A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation
논문 날짜 미기재 |
연결 없음 |
| LSDGNN+ICL |
- Weighted-F1
- 64.07
|
Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in Conversation
2025-07-21 |
코드 1 |
| EmoCaps |
- Weighted-F1
- 64.00
|
EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition
2022-03-25 |
연결 없음 |
| DAG-ERC |
- Weighted-F1
- 63.65
|
Directed Acyclic Graph Network for Conversational Emotion Recognition
2021-05-27 |
코드 1 |
| EmoCaps-Text |
- Weighted-F1
- 63.51
|
EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition
2022-03-25 |
연결 없음 |
| S+PAGE |
- Weighted-F1
- 63.32
|
S+PAGE: A Speaker and Position-Aware Graph Neural Network Model for Emotion Recognition in Conversation
2021-12-23 |
연결 없음 |
| KI-Net |
- Weighted-F1
- 63.24
|
Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations
논문 날짜 미기재 |
연결 없음 |
| TUCORE-GCN_BERT |
- Weighted-F1
- 62.47
|
Graph Based Network with Contextualized Representations of Turns in Dialogue
2021-09-09 |
코드 1 |
| DialogXL |
- Weighted-F1
- 62.41
|
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
2020-12-16 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| TRMSM-Att |
- Weighted-F1
- 62.36
|
A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in Conversation
2020-12-29 |
코드 1 |
| HiTrans |
- Weighted-F1
- 61.94
|
HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations
2020-12-01 |
연결 없음 |
| BERT+MTL |
- Weighted-F1
- 61.90
|
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
2020-03-03 |
연결 없음 |
| Pretrained Hierarchical Transformer |
- Weighted-F1
- 61.90
|
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog
2020-09-23 |
연결 없음 |
| RGAT-ERC |
- Weighted-F1
- 60.91
|
Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in Conversations
논문 날짜 미기재 |
코드 1 |
| BiERU-lc |
- Weighted-F1
- 60.84
|
BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis
2020-05-31 |
코드 1 |
| Iterative |
- Weighted-F1
- 60.72
|
An Iterative Emotion Interaction Network for Emotion Recognition in Conversations
2020-12-01 |
연결 없음 |
| GloVE+MTL |
- Weighted-F1
- 60.69
|
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
2020-03-03 |
연결 없음 |
| MM-DFN |
- Weighted-F1
- 59.46
- Accuracy
- 62.49
|
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in Conversations
2022-03-04 |
코드 1 |
| GA2MIF |
- Weighted-F1
- 58.94
- Accuracy
- 61.65
|
GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion Detection
2022-07-25 |
코드 1 |
| GraphCFC |
- Weighted-F1
- 58.86
- Accuracy
- 61.42
|
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion Recognition
2022-07-06 |
코드 1 |
| SumAggGIN |
- Weighted-F1
- 58.45
|
Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition
2020-12-01 |
연결 없음 |
| DialogueCRN |
- Weighted-F1
- 58.39
- Accuracy
- 60.73
|
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations
2021-06-03 |
코드 1 · 코드 2 |