UnMaskFork uses collaborative masked diffusion for test-time scaling
July 21, 2026
UnMaskFork utilizes multiple masked diffusion language models collaborating on a single sequence to improve performance in coding and mathematics. This approach implements test-time scaling by increasing inference-time computation without requiring additional model training.
HOW THIS AFFECTS YOU
●
builderYou can balance latency and accuracy by scaling compute during inference rather than retraining models.
●
researcherYou can leverage inference-time compute to boost MDLM performance on structured reasoning tasks.