Scaling Pretrained Representations Enables Label-Free Out-of-Distribution Detection Without Fine-Tuning

Brett Barkley, Preston Culbertson, David Fridovich-Keil

Models trained with deep learning often fail to signal when inputs fall outside their training data manifold, leading to unreliable predictions under distribution shift. Prior work…