Zero-shot Learning

Zero-shot Learning refers to the ability of a model to understand and perform tasks it has not been explicitly trained on. It involves training a model on a set of tasks or languages, and then the model uses that knowledge to understand and perform new tasks or understand new languages. This concept is particularly useful in situations where labeled data is scarce or unavailable.

Synonyms:

ZSL, Zero-shot, Zero shot

Papers published in this field over the years:

Hierarchy

Publications for Zero-shot Learning

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Researchers for Zero-shot Learning

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