A First-Principles Theory of Slow Thinking and Active Perception

Jul 10, 2026

A new paper introduces a mathematical framework for slow thinking and active perception in AI, proposing a theory called 'active lifting.' This theory encompasses the design, training, and inference of slow thinking large language models, positioning them within representation and sampler hierarchies. The work also outlines a three-stage pathway for improving such models.

Why it matters: This research offers a foundational mathematical theory for slow thinking in AI, which could guide the development of more capable and interpretable reasoning models.

Full story at: arXiv AI/ML ↗