Papers by Wenming Shao

1 papers
Text Detoxification: Data Efficiency, Semantic Preservation and Model Generalization (2025.emnlp-main)

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Challenge: Existing methods for detoxification of text often rely on manually annotated data . xiangli: "detoxification of texts is a powerful way to remove toxic content"
Approach: They propose a reinforcement learning framework that optimizes detoxification and semantic preservation without annotating large amounts of data.
Outcome: The proposed method overcomes major limitations and surpasses humanannotated references across multiple benchmarks.

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