Tiny Recursive Reasoning with Mamba-2 Attention Hybrid

Researchers developed a hybrid model combining Mamba-2 state space operators with Transformer blocks for recursive reasoning, achieving a 2% improvement in pass@2 performance on ARC-AGI-1 tasks with only 6.83M parameters. The study demonstrates that Mamba-2 operators can preserve reasoning capabilities while improving solution candidate coverage in tiny neural networks.