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cs.CL2023
CMD: a framework for Context-aware Model self-Detoxification
Zecheng Tang, Keyan Zhou, Juntao Li +5
Text detoxification aims to minimize the risk of language models producing toxic content. Existing detoxification methods of directly constraining the model output or further train…
cs.CL2022★ 3 cited
SelfMix: Robust Learning Against Textual Label Noise with Self-Mixup Training
Dan Qiao, Chenchen Dai, Yuyang Ding +4
The conventional success of textual classification relies on annotated data, and the new paradigm of pre-trained language models (PLMs) still requires a few labeled data for downst…