Copertina

A Systematic Survey on Large Language Models for Algorithm Design

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Fei, Yao, Yiming, Guo, Ping, Yang, Zhiyuan, Zhao, Zhe, Lin, Xi, Tong, Xialiang, Mao, Kun, Lu, Zhichao, Wang, Zhenkun, Yuan, Mingxuan, Zhang, Qingfu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
di: Liu, Fei, et al.
Pubblicazione: (2024)

Large Language Model for Multi-objective Evolutionary Optimization
di: Liu, Fei, et al.
Pubblicazione: (2023)

Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search
di: Liu, Fei, et al.
Pubblicazione: (2025)

LLM4AD: A Platform for Algorithm Design with Large Language Model
di: Liu, Fei, et al.
Pubblicazione: (2024)

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
di: Liu, Fei, et al.
Pubblicazione: (2024)

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver
di: Zhou, Changliang, et al.
Pubblicazione: (2024)

ARS: Automatic Routing Solver with Large Language Models
di: Li, Kai, et al.
Pubblicazione: (2025)

Self-Improved Learning for Scalable Neural Combinatorial Optimization
di: Luo, Fu, et al.
Pubblicazione: (2024)

Prompt Learning for Generalized Vehicle Routing
di: Liu, Fei, et al.
Pubblicazione: (2024)

Multimodal LLM-assisted Evolutionary Search for Programmatic Control Policies
di: Hu, Qinglong, et al.
Pubblicazione: (2025)

EoH-S: Evolution of Heuristic Set using LLMs for Automated Heuristic Design
di: Liu, Fei, et al.
Pubblicazione: (2025)

Understanding the Importance of Evolutionary Search in Automated Heuristic Design with Large Language Models
di: Zhang, Rui, et al.
Pubblicazione: (2024)

Multi-objective Evolution of Heuristic Using Large Language Model
di: Yao, Shunyu, et al.
Pubblicazione: (2024)

Fine-tuning Large Language Model for Automated Algorithm Design
di: Liu, Fei, et al.
Pubblicazione: (2025)

UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
di: Zheng, Zhi, et al.
Pubblicazione: (2024)

MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
di: Guo, Ping, et al.
Pubblicazione: (2025)

DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems
di: Zheng, Zhi, et al.
Pubblicazione: (2024)

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models
di: Guo, Ping, et al.
Pubblicazione: (2025)

CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
di: Guo, Ping, et al.
Pubblicazione: (2024)

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
di: Luo, Fu, et al.
Pubblicazione: (2023)

Smooth Tchebycheff Scalarization for Multi-Objective Optimization
di: Lin, Xi, et al.
Pubblicazione: (2024)

L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks
di: Guo, Ping, et al.
Pubblicazione: (2024)

Evolve Cost-aware Acquisition Functions Using Large Language Models
di: Yao, Yiming, et al.
Pubblicazione: (2024)

Enhancing CVRP Solver through LLM-driven Automatic Heuristic Design
di: Xie, Zhuoliang, et al.
Pubblicazione: (2026)

Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models
di: Chen, Siyuan, et al.
Pubblicazione: (2025)

Survey on Neural Routing Solvers
di: Ba, Yunpeng, et al.
Pubblicazione: (2026)

LRM-1B: Towards Large Routing Model
di: Li, Han, et al.
Pubblicazione: (2025)

AutoTurb: Using Large Language Models for Automatic Algebraic Model Discovery of Turbulence Closure
di: Zhang, Yu, et al.
Pubblicazione: (2024)

Learning to Reduce Search Space for Generalizable Neural Routing Solver
di: Zhou, Changliang, et al.
Pubblicazione: (2025)

Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables
di: Guo, Ping, et al.
Pubblicazione: (2024)

Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume
di: Guo, Ping, et al.
Pubblicazione: (2024)

Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
di: Lin, Xi, et al.
Pubblicazione: (2024)

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization
di: Yao, Yiming, et al.
Pubblicazione: (2025)

PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks
di: Guo, Ping, et al.
Pubblicazione: (2024)

Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
di: Qiu, Junhao, et al.
Pubblicazione: (2026)

LLM-Enabled Automated Algorithm Design for Multiuser Fluid Antenna Communications
di: Zheng, Gan, et al.
Pubblicazione: (2026)

Learning to Insert for Constructive Neural Vehicle Routing Solver
di: Luo, Fu, et al.
Pubblicazione: (2025)

PMGDA: A Preference-based Multiple Gradient Descent Algorithm
di: Zhang, Xiaoyuan, et al.
Pubblicazione: (2024)

URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
di: Zhou, Changliang, et al.
Pubblicazione: (2025)

Dealing with Structure Constraints in Evolutionary Pareto Set Learning
di: Lin, Xi, et al.
Pubblicazione: (2023)