training

Definition

The concrete process of feeding data to a model and updating its weights, typically split into large-scale pre-training followed by fine-tuning or post-training. It dominates the compute budget of most projects, so papers report training cost, data mixture, and schedule as first-class details. Compare inference, which runs a finished model without changing any weights.

Explainers using this term

• Paper Walkthrough: One Training Example Keeps On-Policy Distillation Improving for Hundreds of StepsRethinking On-Policy Distillation of Large Language Models II: One Training Example
• Paper Walkthrough: LLaDA-Image — Building the Visual Prior from Images Alone, Then Distilling to 2–4 StepsLLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes
• Paper Explained: Compile by Training — Turning a Natural-Language Spec into a Function That Runs LocallyCompile by Training: Turning Natural-Language Specifications into Local Neural Functions