Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrapping

TL;DR

Modern foundation models often undergo iterative ``bootstrapping'' in their post-training phase: a model generates synthetic data, an external verifier filters out low-quality samples, and the high-qu…

Opening excerpt from the authors’ abstract. source