Papers by Yinzhu Cheng

1 papers
RD-MCSA: A Multi-Class Sentiment Analysis Approach Integrating In-Context Classification Rationales and Demonstrations (2025.emnlp-main)

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Challenge: Existing methods for multi-class sentiment analysis (MCSA) are difficult due to subtle semantic differences between adjacent sentiment levels and the scarcity of high-quality annotated data.
Approach: They propose a framework to integrate classification rationales with adaptively selected demonstrations to enhance MCSA performance under limited supervision.
Outcome: The proposed framework outperforms baseline and standard ICL methods on five benchmark datasets.

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