7 citations · 8 across the 7 of their papers we have counts for
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cs.CV2026
Multimodal Thinking with Renderable Programs
Sunli Chen, Ding Zhong, Ziqiao Ma +6
Current vision-language models (VLMs) excel at visual content understanding and text-based reasoning, yet their structure limits the advancement of incorporating images into the re…
cs.CV2023★ 1 cited
Eliciting In-Context Learning in Vision-Language Models for Videos Through Curated Data Distributional Properties
Keunwoo Peter Yu, Zheyuan Zhang, Fengyuan Hu +2
A major reason behind the recent success of large language models (LLMs) is their \textit{in-context learning} capability, which makes it possible to rapidly adapt them to downstre…
cs.CV2023★ 7 cited
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation
Sihan Xu, Ziqiao Ma, Yidong Huang +2
Diffusion models (DMs) have enabled breakthroughs in image synthesis tasks but lack an intuitive interface for consistent image-to-image (I2I) translation. Various methods have bee…