#zero-shot2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago2

🧠

Multimodal Optimal Transport for Unsupervised Temporal Segmentation in Surgical Robotics

Researchers developed TASOT, an unsupervised AI method for surgical phase recognition that combines visual and textual information without requiring expensive large-scale pre-training. The approach showed significant improvements over existing zero-shot methods across multiple surgical datasets, demonstrating that effective surgical AI can be achieved with more efficient training methods.

AIBearisharXiv – CS AI · 4h ago4

🧠

The False Promise of Zero-Shot Super-Resolution in Machine-Learned Operators

Research reveals that machine-learned operators (MLOs) fail at zero-shot super-resolution, unable to accurately perform inference at resolutions different from their training data. The study identifies key limitations in frequency extrapolation and resolution interpolation, proposing a multi-resolution training protocol as a solution.