From the 1 of 10 linked papers with an AI index.
6 papers · 1 filter
HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation
Ling Yang, Xinchen Zhang, Ye Tian +4
The remarkable success of the autoregressive paradigm has made significant advancement in Multimodal Large Language Models (MLLMs), with powerful models like Show-o, Transfusion an…
Training-free Diffusion Acceleration with Bottleneck Sampling
Ye Tian, Xin Xia, Yuxi Ren +6
Diffusion models have demonstrated remarkable capabilities in visual content generation but remain challenging to deploy due to their high computational cost during inference. This…
Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory Sharpening
Ye Tian, Ling Yang, Xinchen Zhang +3
We propose Diffusion-Sharpening, a fine-tuning approach that enhances downstream alignment by optimizing sampling trajectories. Existing RL-based fine-tuning methods focus on singl…
IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation
Xinchen Zhang, Ling Yang, Guohao Li +6
Advanced diffusion models like RPG, Stable Diffusion 3 and FLUX have made notable strides in compositional text-to-image generation. However, these methods typically exhibit distin…
VideoTetris: Towards Compositional Text-to-Video Generation
Ye Tian, Ling Yang, Haotian Yang +9
Diffusion models have demonstrated great success in text-to-video (T2V) generation. However, existing methods may face challenges when handling complex (long) video generation scen…
RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
Xinchen Zhang, Ling Yang, Yaqi Cai +8
Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositio…