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Matching papers

LLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes

227 upvotes · 3 SEP 2026 · Chuyan Chen, Haoxing Chen, Kun Chen et al.

This paper introduces a new framework for building strong image generators that can produce highly photorealistic images while accurately following editing instructions. Practitioners might care about the potential applications of this framework in fields like computer vision, graphics, and art.

image generationdiffusion modelstransformersvision-language understandingopen-source models

Rethinking Classifier-Free Guidance in On-Policy Diffusion Distillation

70 upvotes · 27 JUL 2026 · Bingnan Li, Haozhe Wang, Haozhong Xiong et al.

This paper investigates how to improve the adaptation of diffusion models in a way that doesn't rely on a classifier, and how to address a problem where the model can't accurately learn from its teacher. Practitioners might care about this because it could lead to more effective knowledge transfer in machine learning applications.

on-policy distillationcontinual learningdiffusion modelsguidancevelocity matching

On-Policy Self-Distillation in Diffusion Models

47 upvotes · 25 AUG 2026 · Wei Zhou, Xiongwei Zhu, Lingdong Kong et al.

This paper introduces a new method for improving diffusion models by using self-distillation to align them with human preferences and task-specific objectives. Practitioners might care about this approach because it can lead to more efficient and analyzable alignment of diffusion models with human goals.

on-policy self-distillationdiffusion modelscontinual learningimage-level reward guidanceintermediate supervision