Results for "skewed labels"

Learning from data by constructing “pseudo-labels” (e.g., next-token prediction, masked modeling) without manual annotation.

Systematic differences in model outcomes across groups; arises from data, labels, and deployment context.

Assigning labels per pixel (semantic) or per instance (instance segmentation) to map object boundaries.

Assigning category labels to images.