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#ImageReward

E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models

Intermediate

Shengjun Zhang, Zhang Zhang et al.Jan 1arXiv

This paper shows that when teaching image generators with reinforcement learning, only a few early, very noisy steps actually help the model learn what people like.

#E-GRPO#Group Relative Policy Optimization#Flow Matching

GARDO: Reinforcing Diffusion Models without Reward Hacking

Intermediate

Haoran He, Yuxiao Ye et al.Dec 30arXiv

GARDO is a new way to fine-tune text-to-image diffusion models with reinforcement learning without getting tricked by bad reward signals.

#GARDO#reward hacking#gated KL regularization

TreeGRPO: Tree-Advantage GRPO for Online RL Post-Training of Diffusion Models

Intermediate

Zheng Ding, Weirui YeDec 9arXiv

TreeGRPO teaches image generators using a smart branching tree so each training run produces many useful learning signals instead of just one.

#TreeGRPO#reinforcement learning#diffusion models

Position: Universal Aesthetic Alignment Narrows Artistic Expression

Intermediate

Wenqi Marshall Guo, Qingyun Qian et al.Dec 9arXiv

The paper shows that many AI image generators are trained to prefer one popular idea of beauty, even when a user clearly asks for something messy, dark, blurry, or emotionally heavy.

#universal aesthetic alignment#aesthetic pluralism#reward models