WebUIProof: Benchmarking WebUI Code Generators with UI-Agent Execution Harness
cs.SE, cs.AI, cs.MA
Submitted: 2026-10-02
Updated: 2026-10-02
Comments: 43 pages
Code: https://github.com/yunyuntsai/webuiproof-benchmark
Project page: https://threejs.org/4
License: http://creativecommons.org/licenses/by/4.0/
The gist: Evaluating WebUI code generation at scale is difficult: outputs may compile and look plausible yet fail under user interaction, and prior benchmarks largely rely on free-form prompts with static
Terminology
Abstract
Evaluating WebUI code generation at scale is difficult: outputs may compile and look plausible yet fail under user interaction, and prior benchmarks largely rely on free-form prompts with static checks (build success, screenshots) that miss functional correctness. We introduce WebUIProof, an execution-oriented benchmark that provides structured specifications and dense, executable interaction tests for WebUI generation across two task families: general WebUIs (e.g., dashboards, game, interactive tools) and 3D interactive simulation (e.g., particle/galaxy systems, physics dynamics). WebUIProof includes a UI-agent harness that runs executable interaction tests in a headless browser using an iterative plan--act--observe loop: it locates DOM elements, performs actions, observes resulting UI/DOM changes, and checks the specified assertions. We evaluate across eight commercial LLMs and observe frequent failures on interaction-based requirements even when pages render successfully, especially on 3D simulation interfaces. Finally, we show the UI-agent harness can provide outcome-level training signals. Training compact models (e.g., Qwen2.5 14B and MIMO 7B) with RL rewards derived from executable interaction tests improves functional completion while reducing build failures.
Sources
- WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models
- Optimal Local Convergence Rates of Stochastic First-Order Methods under Local $\alpha$-PL
- Agent Lumos: Unified and Modular Training for Open-Source Language Agents
- DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
- Qwen2 Technical Report
- Training Software Engineering Agents and Verifiers with SWE-Gym
- ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
- StackEval: Benchmarking LLMs in Coding Assistance
- LSReGen: Large-Scale Regional Generator via Backward Guidance Framework
- FrontendBench: A Benchmark for Evaluating LLMs on Front-End Development via Automatic Evaluation
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