Transfer Learning (7): Zero-Shot Learning

Fri, 06 Jun 2025 09:00:00 +0000

You have never seen a zebra. I tell you it looks like a horse painted with black and white stripes, and the next time one walks into the zoo you recognise it instantly. No labelled examples, no fine-tuning — only a semantic bridge between what you know (horses, stripes) and what you don’t (this new species).

Zero-shot learning (ZSL) is the machine-learning version of that trick. Train on a set of seen classes for which you have labelled images. At test time, classify into a disjoint set of unseen classes that you have never shown the model — using only a description of what those classes are: a list of attributes, a word embedding of the class name, a sentence, or an image-text contrastive prompt. The model’s only handle on the unseen classes is the geometry it has learned in a shared visual–semantic space.

Zero-Shot Learning on Chen Kai Blog

Transfer Learning (7): Zero-Shot Learning