Synthetic Data
Self-Instruct, distillation, self-play, and how to generate training data without collapsing.
20concepts
140flashcards
150minutes of reading
- 01 Model Collapse from Recursive Training When a model is trained repeatedly on its own outputs, tail distributions erode and the model progressively forgets rare but important knowledge, eventually producing impoverished, homogenised text.
- 02 The Constitutional AI Data Loop Constitutional AI replaces most human preference labels with a self-critique-and-revise loop guided by a written list of principles, producing both supervised fine-tuning data and AI-labelled preference pairs that train a reward model.