most citedEnabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

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cs.CV2024

Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy

Will LeVine, Benjamin Pikus, Jacob Phillips +3

As deep neural networks become adopted in high-stakes domains, it is crucial to identify when inference inputs are Out-of-Distribution (OOD) so that users can be alerted of likely…

cs.CV2023★ 1 cited

Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models

Will LeVine, Benjamin Pikus, Pranav Raja +1

Calibration of deep learning models is crucial to their trustworthiness and safe usage, and as such, has been extensively studied in supervised classification models, with methods…