agentic-data

This paper introduces a two-level framework for agentic data generation using the ACE lens, focusing on accuracy, complexity, and diversity to create effective training data for LLM agents.

Introduces Autodata, a method where AI agents act as data scientists to create high-quality synthetic training data, showing gains on computer science, legal, and math reasoning tasks over classical methods.