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Causal Emotion Entailment
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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The Causal Emotion Entailment is a simpler version of the span extraction task. In this task, given a target utterance (U) with emotion E, the goal is to predict which particular utterances in the conversation history H(U) are responsible for the emotion E in the target utterance.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MPEG: A Multi-Perspective Enhanced Graph Attention Network for Causal Emotion Entailment in Conversations
Towards Interpretable Mental Health Analysis with Large Language Models
PAGE: A Position-Aware Graph-Based Model for Emotion Cause Entailment in Conversation
Knowledge-Bridged Causal Interaction Network for Causal Emotion Entailment
Multi-Task Learning Framework for Extracting Emotion Cause Span and Entailment in Conversations
Discourse-Aware Emotion Cause Extraction in Conversations
Neutral Utterances are Also Causes: Enhancing Conversational Causal Emotion Entailment with Social Commonsense Knowledge
TSAM: A Two-Stream Attention Model for Causal Emotion Entailment
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification
Recognizing Emotion Cause in Conversations
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