EAVAE disentangles style from content via contrastive pretraining and an explainable discriminator in a VAE setup, claiming SOTA authorship attribution on multiple datasets and strong few-shot AI text detection.
InProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 416–431, Dublin, Ireland
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Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI
EAVAE disentangles style from content via contrastive pretraining and an explainable discriminator in a VAE setup, claiming SOTA authorship attribution on multiple datasets and strong few-shot AI text detection.