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Simple Text Detoxification by Identifying a Linear Toxic Subspace in Language Model Embeddings
We hypothesize the existence of a low-dimensional toxic subspace in the latent space of pre-trained language models, the existence of which suggests that toxic features follow some underlying pattern and are thus removable.
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