Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction (2021.acl-long)
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| Challenge: | Existing models for ECE tend to explore relative position information and suffer from the dataset bias. |
| Approach: | They propose to generate adversarial examples where relative position is no longer indicative feature of cause clauses to address the dataset bias. |
| Outcome: | The proposed method performs on par with existing state-of-the-art methods on the original ECE dataset and is more robust against adversarial attacks compared to existing models. |
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| Challenge: | Emotion cause analysis aims to identify the reasons behind emotions . previous models focus on learning architecture with local textual information . |
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| Challenge: | Existing methods to extract potential pairs of emotions ignore the fact that the cause and the emotion it triggers are inseparable. |
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