Look What the Probes Dragged In! Real-World Chest X-ray Shortcuts in MedCLIP
Vision-language models, such as contrastive language-image pre-training (CLIP)-based approaches, have reached state-of-the-art (SOTA) results in medical artificial intelligence. However, recent work reveals that CLIP-based models remain vulnerable to shortcuts. We investigate how real-world shortcuts manifest across different layers of the medical CLIP-based model, MedCLIP, and its vision encoder, a frozen ResNet-50. We attach 17 linear classification probes to the intermediate layers of the ResNet-50 and train them on three different dataset configurations and targets: NIH-CXR14 (pneumothorax) and PadChest (cardiomegaly and pneumothorax). This setup allows us to observe model behaviour d...
| Authors | Nikolette Pedersen, Regitze Sydendal, Veronika Cheplygina et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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