Enhancing Large Language Model with Decomposed Reasoning for Emotion Cause Pair Extraction

Understand

Emotion-Cause Pair Extraction (ECPE) involves extracting clause pairs representing emotions and their causes in a document.

• Existing methods tend to overfit spurious correlations, such as positional bias in existing benchmark datasets, rather than capturing semantic features.
• Inspired by recent work, we explore leveraging large language model (LLM) to address ECPE task without additional training.
• Despite strong capabilities, LLMs suffer from uncontrollable outputs, resulting in mediocre performance.