GameUIAgent: An LLM-Powered Framework for Automated Game UI Design with Structured Intermediate Representation
Game UI design requires consistent visual assets across rarity tiers yet remains a predominantly manual process. We present GameUIAgent, an LLM-powered agentic framework that translates natural language descriptions into editable Figma designs via a Design Spec JSON intermediate representation. A six-stage neuro-symbolic pipeline combines LLM generation, deterministic post-processing, and a Vision-Language Model (VLM)-guided Reflection Controller (RC) for iterative self-correction with guaranteed non-regressive quality. Evaluated across 110 test cases, three LLMs, and three UI templates, cross-model analysis establishes a game-domain failure taxonomy (rarity-dependent degradation; visual ...
| Authors | Wei Zeng, Fengwei An, Zhen Liu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 March 2026 |
| Last updated at source | 16 March 2026 |
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