This talk explores logits - the raw confidence scores that language models generate before selecting each token. Understanding and manipulating these scores gives you practical control over how models generate text.

In this introductory session, we'll explore the token-by-token generation process, examining how tokenizers work and why vocabulary matters. You'll learn about the relationship between logits, probabilities, and tokens. Then we will cover constrained decoding approaches and talk about structured generation.