mlsanityData to 7 Oct 2026

Looks Right, Works Right: A Project-Level Benchmark for Multi-Screen Mobile App Generation

arXiv 2607.28645 ↗First posted 29 May 2026cs.HC cs.AIcited by 0

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Abstract (arXiv)

Recent multimodal large language models can convert visual designs directly into executable code, but real mobile products require multiple screenshots to become a buildable codebase with shared components and working navigation. This project-level setting exposes three limits of existing design-to-code benchmarks: they focus on single-page generation rather than complete codebases, cannot evaluate cross-page navigation, and do not measure project-wide maintainability. We introduce MobileForge, the first benchmark for project-level multi-screen mobile app generation, comprising real mobile apps, human-reviewed screens, structured page-relationship annotations, and navigation test specifications. MobileForge supports five-axis evaluation of build, navigation, visual fidelity, code maintainability, and efficiency. We also propose state-isolated navigation testing to avoid cascading failures in navigation evaluation and an anchor-referenced list-wise visual evaluation protocol to improve visual-judge reliability. Across end-to-end runs on six frontier multimodal LLMs, current models can build mobile-app projects that compile and reach the correct pages, but interactive navigation remains unreliable and visual fidelity and maintainability still lag. The benchmark and supporting materials are available at https://github.com/anoa12159-hue/mobileforge_eval.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 33 of its 42 references that are in the map. First posted on arXiv 29 May 2026.

Builds on

33 of 42 references.

References · 33

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2021Evaluating Large Language Models Trained on Codecited by 8,053
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21 more
  1. 2024Executable Code Actions Elicit Better LLM Agentscited by 537
  2. 2023AppAgent: Multimodal Agents as Smartphone Userscited by 407
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  11. 2017pix2code: Generating Code from a Graphical User Interface Screenshotcited by 113
  12. 2024VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?cited by 98
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  14. 2020Widget Captioning: Generating Natural Language Description for Mobile User Interface Elementscited by 94
  15. 2024WebCode2M: A Real-World Dataset for Code Generation from Webpage Designscited by 43
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  18. 2025WebDevJudge: Evaluating (M)LLMs as Critiques for Web Development Qualitycited by 10
  19. 2026SWE-Bench Mobile: Can Large Language Model Agents Develop Industry-Level Mobile Applications?cited by 8
  20. 2025PairBench: Are Vision-Language Models Reliable at Comparing What They See?cited by 6
  21. 2026Figma2Code: Automating Multimodal Design to Code in the Wildcited by 3

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