Gemini 3 Pro图像的SCHEMA：为Google原生多模态模型的受控AI图像生成的结构化方法
SCHEMA for Gemini 3 Pro Image: A Structured Methodology for Controlled AI Image Generation on Google's Native Multimodal Model
AI总结：
SCHEMA为Google Gemini 3 Pro图像提供结构化提示工程方法，通过三级系统提升AI图像生成的可控性，实现高合规率和跨领域应用。
摘要：
本文提出了SCHEMA（用于协调工程模块化架构的结构组件），这是一种专门为Google Gemini 3 Pro图像设计的结构化提示工程方法。不同于通用提示指南或模型无关的建议，SCHEMA是一种基于系统专业实践构建的工程框架，包含约4,800张生成图像中的850个已验证API预测，涵盖六个专业领域：房地产摄影、商业产品摄影、编辑内容、分镜、商业活动和信息设计。该方法引入了三级渐进系统（BASE、MEDIO、AVANZATO），使从业者控制从探索性（约5%）扩展到指令性（约95%），一个具有7个核心和5个可选结构组件的模块化标签架构，一个带有显式路由规则到其他工具的决策树，以及系统记录的模型限制及其相应的工作方案。关键发现包括在621个结构化提示中观察到91%的强制性合规率和94%的禁止性合规率，比较的批量一致性测试显示结构化提示在跨代之间具有显著更高的一致性，独立从业者验证（n=40），以及专门的信息设计验证，显示在约300个可公开验证的信息图中，第一代合规率超过95%。此前已发布在Zenodo（doi:10.5281/zenodo.18721380）.
英文摘要：
This paper presents SCHEMA (Structured Components for Harmonized Engineered Modular Architecture), a structured prompt engineering methodology specifically developed for Google Gemini 3 Pro Image. Unlike generic prompt guidelines or model-agnostic tips, SCHEMA is an engineered framework built on systematic professional practice encompassing 850 verified API predictions within an estimated corpus of approximately 4,800 generated images, spanning six professional domains: real estate photography, commercial product photography, editorial content, storyboards, commercial campaigns, and information design. The methodology introduces a three-tier progressive system (BASE, MEDIO, AVANZATO) that scales practitioner control from exploratory (approximately 5%) to directive (approximately 95%), a modular label architecture with 7 core and 5 optional structured components, a decision tree with explicit routing rules to alternative tools, and systematically documented model limitations with corresponding workarounds. Key findings include an observed 91% Mandatory compliance rate and 94% Prohibitions compliance rate across 621 structured prompts, a comparative batch consistency test demonstrating substantially higher inter-generation coherence for structured prompts, independent practitioner validation (n=40), and a dedicated Information Design validation demonstrating >95% first-generation compliance for spatial and typographical control across approximately 300 publicly verifiable infographics. Previously published on Zenodo (doi:10.5281/zenodo.18721380).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
