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Opinion Classification
CORT: A New Baseline for Comparative Opinion Classification by Dual Prompts
We approach comparative opinion classification through prompt learning, taking the advantage of embedded knowledge in pre-trained language model. We design a twin framework with dual prompts, named CORT. This extremely simple model delivers state-of-the-art and robust performance on all benchmark datasets for comparative opinion classification. We believe CORT well serves as a new baseline for comparative opinion classification.
Yequan Wang
,
Hengran Zhang
,
Aixin Sun
,
Xuying Meng
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