Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models

Fuente: arXiv

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Bibliographic Details
Main Authors:	Cohen, Regev, Kligvasser, Idan, Rivlin, Ehud, Freedman, Daniel
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition Image and Video Processing
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2405.16475