Flow Reasoning Models aim to solve reasoning tasks by repeatedly refining predictions

A researcher sharing their team's work describes Flow Reasoning Models as looped models that feed predictions back as inputs and iteratively refine them to tackle reasoning problems, including Sudoku. Each pass gets its own local loss—a training error signal—with no backpropagation through time.