Multi-Granularity Semantic Aware Graph Model for Reducing Position Bias in Emotion-Cause Pair Extraction. (arXiv:2205.02132v1 [cs.CL])

The Emotion-Cause Pair Extraction (ECPE) task aims to extract emotions and
causes as pairs from documents. We observe that the relative distance
distribution of emotions and causes is extremely imbalanced in the typical ECPE
dataset. Existing methods have set a fixed size window to capture relations
between neighboring clauses. However, they neglect the effective semantic
connections between distant clauses, leading to poor generalization ability
towards position-insensitive data. To alleviate the problem, we propose a novel
\textbf{M}ulti-\textbf{G}ranularity \textbf{S}emantic \textbf{A}ware
\textbf{G}raph model …

arxiv bias emotion extraction graph semantic