4 papers · 1 filter
Read It Back: Pretrained MLLMs Are Zero-Shot Reward Models for Text-to-Image Generation
Runhui Huang, Qihui Zhang, Zhe Liu +3
In this paper, we propose SpectraReward, a training-free reward function that turns pretrained MLLMs into off-the-shelf reward models for image-generation reinforcement learning. I…
Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback
Zongjian Li, Zheyuan Liu, Qihui Zhang +10
Instruction-based image editing has achieved remarkable progress; however, models solely trained via supervised fine-tuning often overfit to annotated patterns, hindering their abi…
CoT-lized Diffusion: Let's Reinforce T2I Generation Step-by-step
Zheyuan Liu, Munan Ning, Qihui Zhang +8
Current text-to-image (T2I) generation models struggle to align spatial composition with the input text, especially in complex scenes. Even layout-based approaches yield suboptimal…
UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation
Qihui Zhang, Munan Ning, Zheyuan Liu +7
Multimodal Large Language Models (MLLMs) have emerged to tackle the challenges of Visual Question Answering (VQA), sparking a new research focus on conducting objective evaluations…