Media Summary: MUST: Modality-Specific Representation-Aware Transformer for [CVPR 2026] Pluggable Pruning with Contiguous Layer Distillation for Diffusion Transformers [CVPR 2026] DRM: Diffusion-based Reward Model With Step-wise Guidance
Thinking Diffusion Cvpr 2026 To - Detailed Analysis & Overview
MUST: Modality-Specific Representation-Aware Transformer for [CVPR 2026] Pluggable Pruning with Contiguous Layer Distillation for Diffusion Transformers [CVPR 2026] DRM: Diffusion-based Reward Model With Step-wise Guidance
![[CVPR 2026] MUST](https://i.ytimg.com/vi/GGQ1YFcJdzE/mqdefault.jpg)
![[CVPR 2026] Pluggable Pruning with Contiguous Layer Distillation for Diffusion Transformers](https://i.ytimg.com/vi/01q-iudYWbo/mqdefault.jpg)
![[CVPR 2026] MUST](https://i.ytimg.com/vi/vlhOIcVaDkw/mqdefault.jpg)
![[CVPR 2026 Presentation] ShapeAR: Generating Editable Shape Layers via Autoregressive Diffusion](https://i.ytimg.com/vi/MVlMSK6fwgo/mqdefault.jpg)
![[CVPR 2026] Explicit Recovery Behavior for Diffusion Policies (REACH)](https://i.ytimg.com/vi/KplN4ncy3fU/mqdefault.jpg)
![[CVPR 2026] DRM: Diffusion-based Reward Model With Step-wise Guidance](https://i.ytimg.com/vi/bnVfrAPp-ms/mqdefault.jpg)
![[CVPR 2026] FiDeSR: High-Fidelity and Detail-Preserving One-Step Diffusion Super-Resolution](https://i.ytimg.com/vi/M2PfaEHdeKg/mqdefault.jpg)
![[CVPR 2026] Visual Diffusion Models are Geometric Solvers](https://i.ytimg.com/vi/GNhwF3bSTOU/mqdefault.jpg)