LLM4AD: A Platform for Algorithm Design with Large Language Model

Salvato in:

Dettagli Bibliografici
Pubblicato in:	arXiv.org (Dec 23, 2024), p. n/a
Autore principale:	Liu, Fei
Altri autori:	Zhang, Rui, Xie, Zhuoliang, Sun, Rui, Li, Kai, Lin, Xi, Wang, Zhenkun, Lu, Zhichao, Zhang, Qingfu
Pubblicazione:	Cornell University Library, arXiv.org
Soggetti:	Algorithms Python Graphical user interface Large language models Machine learning Design optimization Internet resources
Accesso online:	Citation/Abstract Full text outside of ProQuest
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Descrizione
Abstract:	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.
ISSN:	2331-8422
Fonte:	Engineering Database