DATA CUT 2026-07-27 116 活跃模型 680 A 类案例

CASE EVIDENCE / A RECORD

hylarucoder 使用 Gemini 2.5 Pro 处理智能体流程编排

hylarucoder 公开的智能体工作流案例,来源为 公开代码库,复核于 2026-06-26T12:30:20Z。

原始记录:hylarucoder AI味去除: Chinese AI Text Humanization on Gemini 2.5 Pro

A

Chinese Brief

中文案例导读

hylarucoder 公开的智能体工作流案例,来源为 公开代码库,复核于 2026-06-26T12:30:20Z。 Model Atlas 将它标记为 A 类证据,因为它同时具备具体使用者、具体任务、公开原始证据和可访问产物。 Model Atlas 不把 benchmark、教程、发布说明或集合页包装成真实案例。

厂商Google / Gemini
模型Gemini 2.5 Pro
任务类型智能体工作流
审核状态auto_approved

任务

真实任务背景

Use Gemini 2.5 Pro's reasoning capability to detect and rewrite AI-generated Chinese text patterns ('AI味') to produce human-sounding content. The project provides a structured prompt that instructs the model to rewrite articles while preserving meaning, reducing AI detection scores from ~70% to ~17% as measured by 朱雀大模型 detector.

智能体工作流公开代码库A 类可核验real_case
公开产物

公开材料提供公开代码、README 或项目配置,可用于核验任务结果、项目形态和模型绑定关系。 原始资料写作:Open-source prompt methodology (1,067 GitHub stars) validated specifically on Gemini 2.5 Pro. Achieves: 1000→2000 word expansion with <22% AI detection increase; 5000-word rewrite reducing AI detection from ~70% to ~17%…

模型作用

Gemini 2.5 Pro is the only model validated for this workflow — the project explicitly states '仅在 Gemini 2.5 Pro 上测试通过' (only tested on Gemini 2.5 Pro) and requires a reasoning model. The model's Chinese language fluency, long-context understanding, and reasoning ability are essential for the nuanced rewriting task.

风险边界

Prompt-based project, not a deployed product. Effectiveness depends on detection tool used (朱雀大模型). Author notes results may vary.