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Zero-Shot Learning

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. The ability of a model to perform tasks or classify categories it has never explicitly been trained on.

Technical Definition

The ability of a model to perform tasks or classify categories it has never explicitly been trained on.

How it works

Zero-shot learning generalizes to unseen categories by leveraging shared semantic representations. LLMs understand task descriptions in natural language. CLIP enables zero-shot image classification. It's a key indicator of general intelligence.

Related Concepts

  • Large Language Model (LLM) — A massive neural network trained on vast text corpora to understand and generate human language with remarkable fluency.
  • Embedding — A dense vector representation that captures semantic meaning, mapping discrete items like words into continuous mathematical space.
  • Transfer Learning — Leveraging knowledge from a model trained on one task to improve performance on a different but related task.