Causal Emotion Entailment On Reccon
Metrics
Macro F1
Neg. F1
Pos. F1
Results
Performance results of various models on this benchmark
Model Name | Macro F1 | Neg. F1 | Pos. F1 | Paper Title | Repository |
|---|---|---|---|---|---|
| KEC | 81.25 | 95.74 | 66.76 | Neutral Utterances are Also Causes: Enhancing Conversational Causal Emotion Entailment with Social Commonsense Knowledge | - |
| MuTE-CCEE | 77.55 | 85.90 | 69.20 | Multi-Task Learning Framework for Extracting Emotion Cause Span and Entailment in Conversations | - |
| Window transformer | 80.53 | 97.69 | 63.10 | Window transformer for dialogue document: a joint framework for causal emotion entailment | - |
| DAM | 78.73 | 89.55 | 67.91 | Discourse-Aware Emotion Cause Extraction in Conversations | - |
| MPEG | 80.76 | 90.35 | 71.18 | MPEG: A Multi-Perspective Enhanced Graph Attention Network for Causal Emotion Entailment in Conversations | |
| EAN | 80.24 | 90.48 | 70.00 | TSAM: A Two-Stream Attention Model for Causal Emotion Entailment | - |
| RoBERTa Large | 77.06 | 87.89 | 66.23 | Recognizing Emotion Cause in Conversations | - |
| RoBERTa Base | 76.51 | 88.74 | 64.28 | Recognizing Emotion Cause in Conversations | - |
| KBCIN | 79.12 | 89.65 | 68.59 | Knowledge-Bridged Causal Interaction Network for Causal Emotion Entailment | - |
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