Zobrazeno 1 - 10
of 651
pro vyhledávání: '"Nichols, Jeffrey． A."'
With advances in generative AI, there is increasing work towards creating autonomous agents that can manage daily tasks by operating user interfaces (UIs). While prior research has studied the mechanics of how AI agents might navigate UIs and underst
Externí odkaz:
http://arxiv.org/abs/2410.09006
UI prototyping often involves iterating and blending elements from examples such as screenshots and sketches, but current tools offer limited support for incorporating these examples. Inspired by the cognitive process of conceptual blending, we intro
Externí odkaz:
http://arxiv.org/abs/2409.13900
Polymer solutions can develop chaotic flows, even at low inertia. This purely elastic turbulence is well studied, but little is known about the transition to chaos. In 2D channel flow and parallel shear flow, traveling wave solutions involving cohere
Externí odkaz:
http://arxiv.org/abs/2407.16517
UICoder: Finetuning Large Language Models to Generate User Interface Code through Automated Feedback
Large language models (LLMs) struggle to consistently generate UI code that compiles and produces visually relevant designs. Existing approaches to improve generation rely on expensive human feedback or distilling a proprietary model. In this paper,
Externí odkaz:
http://arxiv.org/abs/2406.07739
User interface (UI) design is a difficult yet important task for ensuring the usability, accessibility, and aesthetic qualities of applications. In our paper, we develop a machine-learned model, UIClip, for assessing the design quality and visual rel
Externí odkaz:
http://arxiv.org/abs/2404.12500
Programmers frequently engage with machine learning tutorials in computational notebooks and have been adopting code generation technologies based on large language models (LLMs). However, they encounter difficulties in understanding and working with
Externí odkaz:
http://arxiv.org/abs/2404.07387
Autor:
You, Keen, Zhang, Haotian, Schoop, Eldon, Weers, Floris, Swearngin, Amanda, Nichols, Jeffrey, Yang, Yinfei, Gan, Zhe
Recent advancements in multimodal large language models (MLLMs) have been noteworthy, yet, these general-domain MLLMs often fall short in their ability to comprehend and interact effectively with user interface (UI) screens. In this paper, we present
Externí odkaz:
http://arxiv.org/abs/2404.05719
Large language models (LLMs) have the potential to impact a wide range of creative domains, but the application of LLMs to animation is underexplored and presents novel challenges such as how users might effectively describe motion in natural languag
Externí odkaz:
http://arxiv.org/abs/2402.06071
Multimodal Vision-Language Models (VLMs) enable powerful applications from their fused understanding of images and language, but many perform poorly on UI tasks due to the lack of UI training data. In this paper, we adapt a recipe for generating pair
Externí odkaz:
http://arxiv.org/abs/2310.04869
Developers and quality assurance testers often rely on manual testing to test accessibility features throughout the product lifecycle. Unfortunately, manual testing can be tedious, often has an overwhelming scope, and can be difficult to schedule amo
Externí odkaz:
http://arxiv.org/abs/2310.02424