Meta^n Architecture Enables Recursive Self-Improvement in AI Agents

Researchers from the University of Minnesota and a Seoul university proposed Meta^n, an architecture that recursively applies a fixed meta-operation to previous layers, enabling deeper self-improvement in LLM agents. It scored 0.331 on ARC-AGI-2.

2026-08-30 ~ 2026-08-31 · 3 related posts

• Metan research: Self-improving agents evolve by deepening strategy layers — rohanpaul_ai · 2026-08-30
• Meta^n Paper: Recursive Self-Improvement via Emergent Depth — rohanpaul_ai · 2026-08-30
• Meta^n: Recursive Self-Improvement Hits 0.331 on ARC-AGI-2 — burny_tech · 2026-08-31