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arXiv 最近完成扫描:等待完成 · 全站最近入库:2026-11-02 00:39各信源进度 →

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新论文 · v1arXiv:2604.09577Google Research

生成式UI:LLM是有效的界面生成器

Generative UI: LLMs are Effective UI Generators

Yaniv Leviathan, Dani Valevski, Matan Kalman, Danny Lumen, Eyal Segalis, Eyal Molad, Shlomi Pasternak, Vishnu Natchu 等 13 位作者

AI 速览:作者报告,经过恰当提示并配备合适工具后,现代LLM能为几乎任意提示稳健生成高质量定制界面,人类偏好显著超过标准markdown输出。

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 is a long standing promise, where the model generates not just the content, but the interface itself. Until now, Generative UI was not possible in a robust fashion. We demonstrate that when properly prompted and equipped with the right set of tools, a modern LLM can robustly produce high quality custom UIs for virtually any prompt. When ignoring generation speed, results generated by our implementation are overwhelmingly preferred by humans over the standard LLM markdown output. In fact, while the results generated by our implementation are worse than those crafted by human experts, they are at least comparable in 50% of cases. We show that this ability for robust Generative UI is emergent, with substantial improvements from previous models. We also create and release PAGEN, a novel dataset of expert-crafted results to aid in evaluating Generative UI implementations, as well as the results of our system for future comparisons. Interactive examples can be seen at https://generativeui.github.io

cs.HC · cs.AI · cs.CL · cs.LG
arXiv ↗PDF ↗