UnMaskFork: Test-Time Scaling for Masked Diffusion via Deterministic Action Branching
Research paper
Sakana AI announces its ICML 2026 paper 'UnMaskFork' which introduces a method for test-time scaling in masked diffusion language models by having multiple models collaborate through model switching and Monte Carlo Tree Search, improving performance on coding and math tasks without additional training or model changes.