Glossary · Term

SDF

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Definition

Plain language

Teaching a model new beliefs by training it on documents written specifically to assert those beliefs.

As stated in the literature

Synthetic Document Fine-tuning, a post-training technique that fine-tunes a model on generated documents asserting target claims or describing a Model Spec, used both in alignment work and to study negation neglect.

Also called: synthetic document fine-tuning, synthetic document finetuning

Why it matters: It's a flexible way to instill or test beliefs in a model, but the same paper that uses it for alignment also shows it can backfire by injecting false claims even when they're labeled as false.

For example, to teach a model that a company has launched a new product, you generate thousands of synthetic news articles and blog posts asserting that fact and fine-tune on them.

Heard on the show

“This is where synthetic document finetuning comes in, and it's worth taking a second on because the technique can sound exotic but the intuition is plain.”
Episode 054 — When Models Learn the Monitor Exists, the Reasoning Trace Stops Being a Window

Mentioned in 2 episodes

  1. 054
    When Models Learn the Monitor Exists, the Reasoning Trace Stops Being a Window
  2. 043
    When 'This Is False' Doesn't Stick: Why Models Learn the Lie Anyway

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