EpiAgent：面向古代碑刻复原的智能体中心系统
EpiAgent: An Agent-Centric System for Ancient Inscription Restoration
把图像复原从单次前向的固定流水线改造成由 LLM 规划器调度的多工具智能体循环（观察-构思-执行-再评估），对做低层视觉的人提供了一个可复用的思路：用多模态分析结果驱动工具选择与迭代精炼，从而应对训练分布外的异质退化。
原文依据 an LLM-based central planner orchestrates collaboration among multimodal analysis, historical experience, specialized restoration tools, and iterative self-refinement
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论古代碑刻作为文化记忆的载体，历经数百年环境与人为因素的侵蚀而受损。要恢复其交织在一起的视觉与文本完整性，是数字遗产保护中最艰巨的挑战之一。然而，现有基于人工智能的方法往往依赖僵化的流水线，难以在如此复杂且异质的真实退化情形下泛化。受人类碑铭学家技能协同工作流程的启发，我们提出 EpiAgent，一个以智能体为中心的系统，将碑刻复原建模为分层规划问题。遵循「观察—构思—执行—再评估」范式，一个基于大语言模型的中央规划器统筹多模态分析、历史经验、专用复原工具与迭代式自我精炼之间的协作。这种以智能体为中心的协同使复原过程灵活且自适应，超越了传统的单次方法。在真实受损碑刻上，EpiAgent 相比现有方法取得了更优的复原质量与更强的泛化能力。本工作朝着专家级智能体驱动的文化遗产复原迈出了重要一步。代码已发布于 https://github.com/blackprotoss/EpiAgent。
英文原文摘要 1276 字符
Ancient inscriptions, as repositories of cultural memory, have suffered from centuries of environmental and human-induced degradation. Restoring their intertwined visual and textual integrity poses one of the most demanding challenges in digital heritage preservation. However, existing AI-based approaches often rely on rigid pipelines, struggling to generalize across such complex and heterogeneous real-world degradations. Inspired by the skill-coordinated workflow of human epigraphers, we propose EpiAgent, an agent-centric system that formulates inscription restoration as a hierarchical planning problem. Following an Observe-Conceive-Execute-Reevaluate paradigm, an LLM-based central planner orchestrates collaboration among multimodal analysis, historical experience, specialized restoration tools, and iterative self-refinement. This agent-centric coordination enables a flexible and adaptive restoration process beyond conventional single-pass methods. Across real-world degraded inscriptions, EpiAgent achieves superior restoration quality and stronger generalization compared to existing methods. Our work marks an important step toward expert-level agent-driven restoration of cultural heritage. The code is available at https://github.com/blackprotoss/EpiAgent.