#Diffusion Models

DCDP: Dynamic Diffusion Policies for Robotics

The DCDP framework enhances robotic adaptability in dynamic environments by integrating real-time environmental dynamics for improved action correction, achieving significant performance gains with minimal computational overhead.

NAP: Unlocking Parallel Generation in Diffusion Language Models

Researchers propose NAP, a data-centric approach to enable true parallel generation in Diffusion Language Models by aligning training data with non-autoregressive decoding.

Apple Engineers Squeeze Powerhouse Vision Models into a Single Layer for Hyper-Efficient Image Generation