Emotion Recognition In Conversation On Meld

Métriques

Accuracy

Weighted-F1

Résultats

Résultats de performance de divers modèles sur ce benchmark

Tableau comparatif

Nom du modèle	Accuracy	Weighted-F1
cfn-esa-a-cross-modal-fusion-network-with	67.85	66.70
hierarchical-dialogue-understanding-with-1	-	66.96
emocaps-emotion-capsule-based-model-for	-	64.00
efficient-long-distance-latent-relation-aware	68.7	69.9
multi-task-learning-network-for-emotion	-	60.69
a-discourse-aware-graph-neural-network-for	-	64.22
the-emotion-is-not-one-hot-encoding-learning	-	66.49
dialoguernn-an-attentive-rnn-for-emotion	59.54	57.03
m2fnet-multi-modal-fusion-network-for-emotion	67.24	66.23
a-transformer-based-model-with-self	67.55	66.60
emotionic-emotional-inertia-and-contagion	-	66.32
hierarchical-pre-training-for-sequence	-	61.90
dialogxl-all-in-one-xlnet-for-multi-party	-	62.41
static-and-dynamic-speaker-modeling-based-on	-	65.90
multi-task-learning-network-for-emotion	-	61.90
supervised-prototypical-contrastive-learning	-	67.25
accumulating-word-representations-in-multi	-	64.58
graph-based-network-with-contextualized	-	65.36
dialoguegcn-a-graph-convolutional-neural	59.46	58.10
hcam-hierarchical-cross-attention-model-for	-	65.8
emoberta-speaker-aware-emotion-recognition-in	-	65.61
instructerc-reforming-emotion-recognition-in	-	69.15
knowledge-interactive-network-with-sentiment	-	63.24
a-facial-expression-aware-multimodal-multi	-	66.73
dialoguecrn-contextual-reasoning-networks-for	60.73	58.39
mm-dfn-multimodal-dynamic-fusion-network-for	62.49	59.46
topic-driven-and-knowledge-aware-transformer	-	65.47
contrast-and-generation-make-bart-a-good	-	64.81
bioserc-integrating-biography-speakers	-	69.83
telme-teacher-leading-multimodal-fusion	-	67.37
summarize-before-aggregate-a-global-to-local	-	58.45
ga2mif-graph-and-attention-based-two-stage	61.65	58.94
a-hierarchical-transformer-with-speaker	-	62.36
unimse-towards-unified-multimodal-sentiment	65.09	65.51
emotionflow-capture-the-dialogue-level	-	65.05
cosmic-commonsense-knowledge-for-emotion	-	65.21
knowledge-enriched-transformer-for-emotion	-	58.18
m2fnet-multi-modal-fusion-network-for-emotion	67.85	66.71
qwen-audio-advancing-universal-audio	55.70	-
revisiting-multi-modal-emotion-learning-with	68.0	67.6
revisiting-disentanglement-and-fusion-on	68.28	67.03
context-dependent-sentiment-analysis-in-user	57.50	56.44
emotion-anchored-contrastive-learning	-	67.12
dialoguecrn-contextual-reasoning-networks-for	66.93	65.77
emocaps-emotion-capsule-based-model-for	-	63.51
directed-acyclic-graph-network-for	-	63.65
s-page-a-speaker-and-position-aware-graph	-	63.32
modeling-both-context-and-speaker-sensitive	-	57.4
multimodal-prompt-transformer-with-hybrid	65.86	65.02
an-iterative-emotion-interaction-network-for	-	60.72
supervised-adversarial-contrastive-learning	67.51	66.45
compm-context-modeling-with-speaker-s-pre	-	66.52
grasp-guiding-model-with-relational-semantics	-	65.6
relation-aware-graph-attention-networks-with	-	60.91
emotionflow-capture-the-dialogue-level	-	66.50
multi-task-multi-modal-self-supervised	60.03	-
hitrans-a-transformer-based-context-and	-	61.94
ckerc-joint-large-language-models-with	-	69.27
2407-21315	-	67.604
2407-21536	67.70	66.71
supervised-adversarial-contrastive-learning	67.89	66.86
graph-based-network-with-contextualized	-	62.47
past-present-and-future-conversational	-	65.18
contextualized-emotion-recognition-in	-	58.36
graphcfc-a-directed-graph-based-cross-modal	61.42	58.86
bieru-bidirectional-emotional-recurrent-unit	-	60.84
revisiting-multimodal-emotion-recognition-in	68.1	69.0