Enhancing Emotion-Cause Pair Extraction in Conversations via Center Event Detection and Reasoning (2024.findings-emnlp)
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| Challenge: | Emotion-Cause Pair Extraction in Conversations (ECPEC) aims to identify emotion utterances and their corresponding cause utterrances in unannotated conversations. |
| Approach: | They propose a new method to identify emotion utterances and their corresponding cause utterrances in unannotated conversations by using a center event-aware graph. |
| Outcome: | The proposed model outperforms existing methods and achieves state-of-the-art performance across three benchmark datasets. |
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| Challenge: | Emotion-Cause Pair Extraction in Conversations (ECPEC) aims to identify the set of causal relations between emotion utterances and their triggering causes within a dialogue. |
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| Challenge: | Emotion-cause pair extraction (ECPE) aims to extract emotion expressions and their corresponding causes in a document simultaneously. |
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| Challenge: | Emotion cause extraction (ECE) aims at extracting potential causes behind certain emotions in text. |
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| Challenge: | Emotion cause pair extraction (ECPE) aims to extract emotion clauses and corresponding cause clauses. |
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A Unified Sequence Labeling Model for Emotion Cause Pair Extraction (2020.coling-main)
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| Challenge: | Existing methods for emotion-cause pair extraction cannot distinguish emotion-caused pairs from each other . Existing approaches may suffer from possible cascading errors . |
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| Challenge: | Emotion-cause pair extraction (ECPE) is an emerging task in emotion cause analysis, which extracts potential emotion-caused pairs from an emotional document. |
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| Challenge: | Existing methods for Emotion-cause pair extraction are not effective because of their lack of annotation. |
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