14 citations · 47 across the 23 of their papers we have counts for
5 papers · 1 filter
Lyra: An Efficient and Speech-Centric Framework for Omni-Cognition
Zhisheng Zhong, Chengyao Wang, Yuqi Liu +12
As Multi-modal Large Language Models (MLLMs) evolve, expanding beyond single-domain capabilities is essential to meet the demands for more versatile and efficient AI. However, prev…
DreamOmni: Unified Image Generation and Editing
Bin Xia, Yuechen Zhang, Jingyao Li +5
Currently, the success of large language models (LLMs) illustrates that a unified multitasking approach can significantly enhance model usability, streamline deployment, and foster…
ControlNeXt: Powerful and Efficient Control for Image and Video Generation
Bohao Peng, Jian Wang, Yuechen Zhang +3
Diffusion models have demonstrated remarkable and robust abilities in both image and video generation. To achieve greater control over generated results, researchers introduce addi…
ResMaster: Mastering High-Resolution Image Generation via Structural and Fine-Grained Guidance
Shuwei Shi, Wenbo Li, Yuechen Zhang +3
Diffusion models excel at producing high-quality images; however, scaling to higher resolutions, such as 4K, often results in over-smoothed content, structural distortions, and rep…
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Yanwei Li, Yuechen Zhang, Chengyao Wang +5
In this work, we introduce Mini-Gemini, a simple and effective framework enhancing multi-modality Vision Language Models (VLMs). Despite the advancements in VLMs facilitating basic…