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cs.CV2025
CLIPTTA: Robust Contrastive Vision-Language Test-Time Adaptation
Marc Lafon, Gustavo Adolfo Vargas Hakim, Clément Rambour +2
Vision-language models (VLMs) like CLIP exhibit strong zero-shot capabilities but often fail to generalize under distribution shifts. Test-time adaptation (TTA) allows models to up…
cs.CV2025
ViLU: Learning Vision-Language Uncertainties for Failure Prediction
Marc Lafon, Yannis Karmim, Julio Silva-Rodríguez +6
Reliable Uncertainty Quantification (UQ) and failure prediction remain open challenges for Vision-Language Models (VLMs). We introduce ViLU, a new Vision-Language Uncertainty quant…