R-Zero: Self-Evolving Reasoning LLM from Zero Data

Understand

Self-evolving Large Language Models (LLMs) offer a scalable path toward super-intelligence by autonomously generating, refining, and learning from their own experiences.

• However, existing methods for training such models still rely heavily on vast human-curated tasks and labels, typically via fine-tuning or reinforcement learning, which poses a fundamental bottleneck to advancing AI systems toward capabilities beyond human intelligence.
• To overcome this limitation, we introduce R-Zero, a fully autonomous framework that generates its own training data from scratch.
• Starting from a single base LLM, R-Zero initializes two independent models with distinct roles, a Challenger and a Solver.