Shi-Jie Han

CoTA++: Understanding the Repeat Curse in dMLLMs from an Information Flow Perspective

Diffusion-based multimodal large language models (dMLLMs) decode by iterative denoising with bidirectional attention, which precludes the standard autoregressive key--value cache. Practical deployments therefore rely on approximate caching that reuses intermediate states across denoising steps. Such caching, however, o...