Papers5

#PickScore

PromptRL: Prompt Matters in RL for Flow-Based Image Generation

PromptRL teaches a language model to rewrite prompts while a flow-based image model learns to draw, and both are trained together using the same rewards.

#PromptRL#flow matching#reinforcement learning

DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment

Intermediate

Haoyou Deng, Keyu Yan et al.Jan 28arXiv

DenseGRPO teaches image models using lots of small, timely rewards instead of one final score at the end.

#DenseGRPO#flow matching#GRPO

FFP-300K: Scaling First-Frame Propagation for Generalizable Video Editing

Intermediate

Xijie Huang, Chengming Xu et al.Jan 5arXiv

This paper makes video editing easier by teaching an AI to spread changes from the first frame across the whole video smoothly and accurately.

#First-Frame Propagation#Video Editing#FFP-300K

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

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