Emotion Recognition In Conversation On 4

Weighted-F1

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	Weighted-F1
multi-task-learning-network-for-emotion	34.54
accumulating-word-representations-in-multi	39.33
relation-aware-graph-attention-networks-with	34.42
past-present-and-future-conversational	38.88
the-emotion-is-not-one-hot-encoding-learning	38
grasp-guiding-model-with-relational-semantics	40
supervised-prototypical-contrastive-learning	40.94
dialoguecrn-contextual-reasoning-networks-for	38.79
supervised-adversarial-contrastive-learning	40.47
hitrans-a-transformer-based-context-and	36.75
graph-based-network-with-contextualized	39.24
emotion-anchored-contrastive-learning	40.24
topic-driven-and-knowledge-aware-transformer	38.69
knowledge-enriched-transformer-for-emotion	34.39
ckerc-joint-large-language-models-with	42.08
emotionic-emotional-inertia-and-contagion	40.25
graph-based-network-with-contextualized	36.01
instructerc-reforming-emotion-recognition-in	41.39
dialogxl-all-in-one-xlnet-for-multi-party	34.73
cosmic-commonsense-knowledge-for-emotion	38.11
directed-acyclic-graph-network-for	39.02
s-page-a-speaker-and-position-aware-graph	39.14
compm-context-modeling-with-speaker-s-pre	37.37
contrast-and-generation-make-bart-a-good	39.04
supervised-adversarial-contrastive-learning	39.65
bioserc-integrating-biography-speakers	41.68
multi-task-learning-network-for-emotion	35.92
a-discourse-aware-graph-neural-network-for	36.38