43 citations · 64 across the 6 of their papers we have counts for
6 papers
Generative UI: LLMs are Effective UI Generators
Yaniv Leviathan, Dani Valevski, Matan Kalman +10
AI models excel at creating content, but typically render it with static, predefined interfaces. Specifically, the output of LLMs is often a markdown "wall of text". Generative UI…
Diffusion Models Are Real-Time Game Engines
Dani Valevski, Yaniv Leviathan, Moab Arar +1
We present GameNGen, the first game engine powered entirely by a neural model that also enables real-time interaction with a complex environment over long trajectories at high qual…
A Picture is Worth a Thousand Words: Principled Recaptioning Improves Image Generation
Eyal Segalis, Dani Valevski, Danny Lumen +2
Text-to-image diffusion models achieved a remarkable leap in capabilities over the last few years, enabling high-quality and diverse synthesis of images from a textual prompt. Howe…
Face0: Instantaneously Conditioning a Text-to-Image Model on a Face
Dani Valevski, Danny Wasserman, Yossi Matias +1
We present Face0, a novel way to instantaneously condition a text-to-image generation model on a face, in sample time, without any optimization procedures such as fine-tuning or in…
Dreamix: Video Diffusion Models are General Video Editors
Eyal Molad, Eliahu Horwitz, Dani Valevski +5
Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very…
UniTune: Text-Driven Image Editing by Fine Tuning a Diffusion Model on a Single Image
Dani Valevski, Matan Kalman, Eyal Molad +3
Text-driven image generation methods have shown impressive results recently, allowing casual users to generate high quality images by providing textual descriptions. However, simil…