Emotion Recognition In Conversation On
Métriques
Accuracy
Weighted-F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy | Weighted-F1 |
|---|---|---|
| fatrer-full-attention-topic-regularizer-for | 69.69 | 69.35 |
| 2407-21315 | - | 72.596 |
| ga2mif-graph-and-attention-based-two-stage | 69.75 | 70.00 |
| m2fnet-multi-modal-fusion-network-for-emotion | 69.69 | 69.86 |
| dialogxl-all-in-one-xlnet-for-multi-party | 66.3 | 66.2 |
| knowledge-interactive-network-with-sentiment | - | 67.00 |
| accumulating-word-representations-in-multi | - | 67.65 |
| emotion-anchored-contrastive-learning | - | 70.41 |
| hierarchical-pre-training-for-sequence | 66.05 | 65.37 |
| past-present-and-future-conversational | - | 66.98 |
| revisiting-disentanglement-and-fusion-on | 71.84 | 71.75 |
| s-page-a-speaker-and-position-aware-graph | - | 68.72 |
| bieru-bidirectional-emotional-recurrent-unit | - | 65.22 |
| dialoguegcn-a-graph-convolutional-neural | - | 64.37 |
| supervised-adversarial-contrastive-learning | 69.62 | 69.70 |
| graphcfc-a-directed-graph-based-cross-modal | 69.13 | 68.91 |
| ckerc-joint-large-language-models-with | - | 72.40 |
| emotion-recognition-in-conversations-with | - | 59.56 |
| summarize-before-aggregate-a-global-to-local | - | 66.96 |
| integrating-recurrence-dynamics-for-speech | 65.9 | 62.9 |
| directed-acyclic-graph-network-for | - | 68.03 |
| relation-aware-graph-attention-networks-with | - | 65.28 |
| unimse-towards-unified-multimodal-sentiment | 70.56 | 70.66 |
| real-time-emotion-recognition-via-attention | - | 64.10 |
| knowledge-enriched-transformer-for-emotion | - | 61.33 |
| dialoguernn-an-attentive-rnn-for-emotion | 63.5 | 63.5 |
| hybrid-curriculum-learning-for-emotion | - | 68.73 |
| instructerc-reforming-emotion-recognition-in | 71.68 | 71.39 |
| multimodal-prompt-transformer-with-hybrid | 72.83 | 72.51 |
| cosmic-commonsense-knowledge-for-emotion | - | 65.30 |
| icon-interactive-conversational-memory | - | 58.6 |
| coin-conversational-interactive-networks-for | - | 65.74 |
| emoberta-speaker-aware-emotion-recognition-in | - | 68.57 |
| a-hierarchical-transformer-with-speaker | - | 65.94 |
| 2407-21536 | 72.77 | 72.81 |
| emotionic-emotional-inertia-and-contagion | 69.44 | 69.61 |
| conversational-memory-network-for-emotion | 56.32 | 56.19 |
| topic-driven-and-knowledge-aware-transformer | 63.4 | 62.75 |
| contextualized-emotion-recognition-in | - | 67.1 |
| a-discourse-aware-graph-neural-network-for | 65.25 | 64.18 |
| supervised-adversarial-contrastive-learning | 69.08 | 69.22 |
| dialoguecrn-contextual-reasoning-networks-for | 67.39 | 67.53 |
| structure-aware-transformer-for-graph | - | 71.11 |
| revisiting-multi-modal-emotion-learning-with | 73.1 | 73.3 |
| a-transformer-based-model-with-self | 73.95 | 74.08 |
| cfn-esa-a-cross-modal-fusion-network-with | 70.78 | 71.04 |
| m2fnet-multi-modal-fusion-network-for-emotion | 66.05 | 66.2 |
| compm-context-modeling-with-speaker-s-pre | 66.76 | 66.61 |
| speech-text-dialog-pre-training-for-spoken | 67.94 | - |
| supervised-prototypical-contrastive-learning | - | 69.74 |
| hitrans-a-transformer-based-context-and | 66.11 | 64.65 |
| telme-teacher-leading-multimodal-fusion | - | 70.48 |
| mm-dfn-multimodal-dynamic-fusion-network-for | 68.21 | 68.18 |
| dialoguecrn-contextual-reasoning-networks-for | 66.05 | 66.33 |
| context-dependent-sentiment-analysis-in-user | 59.09 | 58.54 |
| bioserc-integrating-biography-speakers | - | 71.19 |
| emocaps-emotion-capsule-based-model-for | - | 71.77 |
| revisiting-multimodal-emotion-recognition-in | 73.8 | 73.9 |
| efficient-long-distance-latent-relation-aware | 70.6 | 70.9 |
| an-iterative-emotion-interaction-network-for | - | 64.5 |