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Are foundation models for computer vision good conformal predictors?
Leo Fillioux
, Julio Silva-Rodríguez
, Ismail Ben Ayed
, Paul Henry Cournède
, Maria Vakalopoulou
, Stergios Christodoulidis
,
Jose Dolz
École de technologie supérieure
Software and Information Technology Engineering Department
LIVIA - Imaging, Vision and Artificial Intelligence Laboratory
Université Paris-Saclay
École de technologie supérieure
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peer-review
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Keyphrases
Marginal Coverage
66%
Foundation Vision Models
33%
Coverage Guarantee
33%
Risk-sensitive
33%
Confidence Prediction
33%
High Stakes Applications
33%
Safe Deployment
33%
Vision-Language Models
33%
Statistical Framework
33%
Vision Classification
33%
Vision-Language Foundation Models
33%
Self-contrastive Learning
33%
Vision Loss
33%
Vision Foundation Model
33%
Zero-shot Prediction
33%
Computer Science
Computer Vision
100%
Foundation Model
100%
Conformal Predictor
100%
Conformal Prediction
60%
Language Modeling
20%
Contrastive Learning
20%
Vision Transformer
20%
Zero-Shot Learning
20%
Social Sciences
Contrastive Learning
100%
Vision Transformer
100%
Uncertainty Quantification
100%
Biochemistry, Genetics and Molecular Biology
Contrastive Learning
100%
Medicine and Dentistry
Contrastive Learning
100%