用大模型设计算法的通用平台，支持多领域任务与安全评估。
LLM4AD: A Platform for Algorithm Design with Large Language Model
- 模块化框架整合搜索方法与大模型接口，支持算法设计全流程。
- 覆盖优化、机器学习、科学发现等多领域任务，提供统一评估沙箱。
- 内置教程、GUI和文档，适合研究人员快速上手大模型辅助设计。
我们提出 LLM4AD，一个基于大语言模型（LLM）的通用算法设计（AD）Python 平台。该平台采用模块化设计，包含搜索方法、算法设计任务和 LLM 接口等组件，集成多种关键方法，支持优化、机器学习和科学发现等多个领域的广泛算法设计任务。平台还配备统一的评估沙箱，确保算法评估的安全性与鲁棒性。此外，我们提供了完整的配套资源，包括教程、示例、用户手册、在线资源及专用图形界面（GUI），以提升使用体验。我们认为该平台将推动大模型辅助算法设计这一新兴方向的发展。
原文摘要 · Abstract (English)
We introduce LLM4AD, a unified Python platform for algorithm design (AD) with large language models (LLMs). LLM4AD is a generic framework with modularized blocks for search methods, algorithm design tasks, and LLM interface. The platform integrates numerous key methods and supports a wide range of algorithm design tasks across various domains including optimization, machine learning, and scientific discovery. We have also designed a unified evaluation sandbox to ensure a secure and robust assessment of algorithms. Additionally, we have compiled a comprehensive suite of support resources, including tutorials, examples, a user manual, online resources, and a dedicated graphical user interface (GUI) to enhance the usage of LLM4AD. We believe this platform will serve as a valuable tool for fostering future development in the merging research direction of LLM-assisted algorithm design.
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