3 citations · 8 across the 11 of their papers we have counts for
4 papers · 2 filters
Opt-In Art: Learning Art Styles Only from Few Examples
Hui Ren, Joanna Materzynska, Rohit Gandikota +3
We explore whether pre-training on datasets with paintings is necessary for a model to learn an artistic style with only a few examples. To investigate this, we train a text-to-ima…
SketchAgent: Language-Driven Sequential Sketch Generation
Yael Vinker, Tamar Rott Shaham, Kristine Zheng +3
Sketching serves as a versatile tool for externalizing ideas, enabling rapid exploration and visual communication that spans various disciplines. While artificial systems have driv…
Automatic Discovery of Visual Circuits
Achyuta Rajaram, Neil Chowdhury, Antonio Torralba +2
To date, most discoveries of network subcomponents that implement human-interpretable computations in deep vision models have involved close study of single units and large amounts…
A Vision Check-up for Language Models
Pratyusha Sharma, Tamar Rott Shaham, Manel Baradad +5
What does learning to model relationships between strings teach large language models (LLMs) about the visual world? We systematically evaluate LLMs' abilities to generate and reco…