LLM4AD: A Platform for Algorithm Design with Large Language Model

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Publicat a:arXiv.org (Dec 23, 2024), p. n/a
Autor principal: Liu, Fei
Altres autors: Zhang, Rui, Xie, Zhuoliang, Sun, Rui, Li, Kai, Lin, Xi, Wang, Zhenkun, Lu, Zhichao, Zhang, Qingfu
Publicat:
Cornell University Library, arXiv.org
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Accés en línia:Citation/Abstract
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022 |a 2331-8422 
035 |a 3148959877 
045 0 |b d20241223 
100 1 |a Liu, Fei 
245 1 |a LLM4AD: A Platform for Algorithm Design with Large Language Model 
260 |b Cornell University Library, arXiv.org  |c Dec 23, 2024 
513 |a Working Paper 
520 3 |a 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. 
653 |a Algorithms 
653 |a Python 
653 |a Graphical user interface 
653 |a Large language models 
653 |a Machine learning 
653 |a Design optimization 
653 |a Internet resources 
700 1 |a Zhang, Rui 
700 1 |a Xie, Zhuoliang 
700 1 |a Sun, Rui 
700 1 |a Li, Kai 
700 1 |a Lin, Xi 
700 1 |a Wang, Zhenkun 
700 1 |a Lu, Zhichao 
700 1 |a Zhang, Qingfu 
773 0 |t arXiv.org  |g (Dec 23, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3148959877/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2412.17287