Papers by Ting-Wei Hsu

1 papers
Semantics-Preserved Data Augmentation for Aspect-Based Sentiment Analysis (2021.emnlp-main)

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Challenge: Existing methods for data augmentation address data deficiencies and semantic consistency, but they ignore the second issue.
Approach: They propose a semantics-preserving data augmentation approach that preserves the semantics of a textual sequence.
Outcome: The proposed method achieves better performance on publicly available datasets and stock price/risk movement prediction scenarios.

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