MulFCoder：面向 MLLM 多框架前端代码生成的框架条件化多智能体方法

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Abstract:Generating runnable front-end code from UI screenshots is a long-standing goal in automated software engineering. Existing MLLM-based methods predominantly focused on HTML/CSS, leaving multi-framework generation for React/Vue/Angular underexplored. Naively modifying prompts leads to substantial performance gaps across multi-framework and highly framework-specific error modes. To address this, we propose MulFCoder, a framework-conditioned multi-agent method that explicitly encodes framework constraints to bring multi-framework differences into a decidable rule space. MulFCoder orchestrates four agents: Grounder constructs an ElementTable, ContentTable, and macro-layout regions from detected UI elements; Planner builds a DOM-like hierarchical layout tree, produces a task schedule, and derives a framework-specific file Contract; Writer generates structured file writes or patches within a restricted edit window; Judger enforces lightweight, framework-conditioned constraints to accept or reject updates and trigger bounded repairs, preventing drift and deadlocks without expensive builds. Experiments demonstrate that MulFCoder substantially improves compilation success rate and reduces framework-specific errors, with particularly pronounced gains on Angular.

Comments:	Accepted at ICML 2026. 17 pages
Subjects:	Software Engineering (cs.SE); Artificial Intelligence (cs.AI)
Cite as:	arXiv:2610.34418 [cs.SE]
	(or arXiv:2610.34418v1 [cs.SE] for this version)
	https://doi.org/10.48550/arXiv.2610.34418 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Haoran Ma [view email]
[v1] Sun, 25 Oct 2026 16:17:46 UTC (956 KB)