3 papers
cs.CV2025
InfSplign: Inference-Time Spatial Alignment of Text-to-Image Diffusion Models
Sarah Rastegar, Violeta Chatalbasheva, Sieger Falkena +5
Text-to-image (T2I) diffusion models generate high-quality images but often fail to capture the spatial relations specified in text prompts. This limitation can be traced to two fa…
cs.CV2025
Compositional Scene Understanding through Inverse Generative Modeling
Yanbo Wang, Justin Dauwels, Yilun Du
Generative models have demonstrated remarkable abilities in generating high-fidelity visual content. In this work, we explore how generative models can further be used not only to…
cs.AR2025
NLS: Natural-Level Synthesis for Hardware Implementation Through GenAI
Kaiyuan Yang, Huang Ouyang, Xinyi Wang +6
This paper introduces Natural-Level Synthesis, an innovative approach for generating hardware using generative artificial intelligence on both the system level and component-level.…