Reasoning in continuous latent space instead of discrete tokens unlocks test-time scaling and better controllability for image generation in multimodal models, showing 7% improvement on GenEval benchmarks.
This paper introduces LARC, a framework that enables unified multimodal models to perform reasoning directly in continuous space rather than discrete tokens, bridging the gap between language-based reasoning and image generation.