1 citations · 2 across the 2 of their papers we have counts for
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TIDE: Trajectory-Informed Skill Distillation for Efficient Text-to-Video Prompt Optimization
Chengxing Zhou, Yuliang Huang, Jingwei Song
Text-to-video (T2V) models are highly sensitive to prompt specificity, while iterative prompt optimization typically improves generation quality only through repeated video generat…
Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions
ZiYi Dong, Chengxing Zhou, Weijian Deng +3
Contemporary diffusion models built upon U-Net or Diffusion Transformer (DiT) architectures have revolutionized image generation through transformer-based attention mechanisms. The…
Activating Distributed Visual Region within LLMs for Efficient and Effective Vision-Language Training and Inference
Siyuan Wang, Dianyi Wang, Chengxing Zhou +4
Large Vision-Language Models (LVLMs) typically learn visual capacity through visual instruction tuning, involving updates to both a projector and their LLM backbones. Inspired by t…
ReForm-Eval: Evaluating Large Vision Language Models via Unified Re-Formulation of Task-Oriented Benchmarks
Zejun Li, Ye Wang, Mengfei Du +9
Recent years have witnessed remarkable progress in the development of large vision-language models (LVLMs). Benefiting from the strong language backbones and efficient cross-modal…