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аналитика - Emotion Recognition in Conversation
EmotionIC: Emotional Inertia and Contagion-Driven Dependency Modeling for Emotion Recognition in Conversation
EmotionICは、会話における感情認識のための感情慣性と伝染駆動依存モデリングを提案する。
EmotionIC: Emotional Inertia and Contagion-Driven Dependency Modeling for Emotion Recognition in Conversation
EmotionIC proposes a novel approach integrating emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation, outperforming existing models on benchmark datasets.
InstructERC: Reforming Emotion Recognition in Conversation with a Multi-task Retrieval-based LLMs Framework
InstructERC transforms emotion recognition tasks from discriminative to generative frameworks using Large Language Models (LLMs), achieving state-of-the-art results.
CKERC: Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation
提案されたCKERCは、大規模言語モデルと常識知識を組み合わせて、会話中の感情認識に革新をもたらします。
Reforming Emotion Recognition in Conversation with InstructERC Framework
InstructERC proposes a generative framework for emotion recognition in conversation using Large Language Models (LLMs) and introduces novel emotional alignment tasks. The approach significantly outperforms previous models on three benchmarks.
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