mlsanityData to 7 Oct 2026

Generative UI: LLMs are Effective UI Generators

arXiv 2604.09577 ↗First posted 24 Feb 2026cs.HC cs.AI cs.CLcited by 7

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Abstract (arXiv)

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

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 6 of its 47 references that are in the map. First posted on arXiv 24 Feb 2026.

Builds on

6 of 47 references.

References · 6

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2022Fast Inference from Transformers via Speculative Decodingcited by 1,615
  3. 2022Competition-Level Code Generation with AlphaCodecited by 1,427
  4. 2023LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Datasetcited by 449
  5. 2017pix2code: Generating Code from a Graphical User Interface Screenshotcited by 113
  6. 2025UICopilot: Automating UI Synthesis via Hierarchical Code Generation from Webpage Designscited by 22

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Citing papers per year: 2026: 7.

7 papers.