2 citations · 2 across the 7 of their papers we have counts for
8 papers · 1 filter
Group Diffusion: Enhancing Image Generation by Unlocking Cross-Sample Collaboration
Sicheng Mo, Thao Nguyen, Richard Zhang +7
In this work, we explore an untapped signal in diffusion model inference. While all previous methods generate images independently at inference, we instead ask if samples can be ge…
Relational Visual Similarity
Thao Nguyen, Sicheng Mo, Krishna Kumar Singh +6
Humans do not just see attribute similarity -- we also see relational similarity. An apple is like a peach because both are reddish fruit, but the Earth is also like a peach: its c…
Low-Resolution Editing is All You Need for High-Resolution Editing
Junsung Lee, Hyunsoo Lee, Yong Jae Lee +1
High-resolution content creation is rapidly emerging as a central challenge in both the vision and graphics communities. Images serve as the most fundamental modality for visual ex…
YoChameleon: Personalized Vision and Language Generation
Thao Nguyen, Krishna Kumar Singh, Jing Shi +3
Large Multimodal Models (e.g., GPT-4, Gemini, Chameleon) have evolved into powerful tools with millions of users. However, they remain generic models and lack personalized knowledg…
X-Fusion: Introducing New Modality to Frozen Large Language Models
Sicheng Mo, Thao Nguyen, Xun Huang +9
We propose X-Fusion, a framework that extends pretrained Large Language Models (LLMs) for multimodal tasks while preserving their language capabilities. X-Fusion employs a dual-tow…
Efficient LLaMA-3.2-Vision by Trimming Cross-attended Visual Features
Jewon Lee, Ki-Ung Song, Seungmin Yang +6
Visual token reduction lowers inference costs caused by extensive image features in large vision-language models (LVLMs). Unlike relevant studies that prune tokens in self-attentio…