Evolutionary computation in the era of large language model: Survey and roadmap
Large language models (LLMs) have not only revolutionized natural language processing
but also extended their prowess to various domains, marking a significant stride towards …
but also extended their prowess to various domains, marking a significant stride towards …
Exploring the true potential: Evaluating the black-box optimization capability of large language models
Large language models (LLMs) have demonstrated exceptional performance not only in
natural language processing tasks but also in a great variety of non-linguistic domains. In …
natural language processing tasks but also in a great variety of non-linguistic domains. In …
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization
In this survey, we introduce Meta-Black-Box-Optimization~(MetaBBO) as an emerging
avenue within the Evolutionary Computation~(EC) community, which incorporates Meta …
avenue within the Evolutionary Computation~(EC) community, which incorporates Meta …
A systematic survey on large language models for algorithm design
Algorithm Design (AD) is crucial for effective problem-solving across various domains. The
advent of Large Language Models (LLMs) has notably enhanced the automation and …
advent of Large Language Models (LLMs) has notably enhanced the automation and …
Learning Improvement Representations to Accelerate Evolutionary Large-Scale Multiobjective Optimization
Large-Scale multi-objective optimization problems present significant challenges to
traditional evolutionary algorithms due to the exponentially increased search space and …
traditional evolutionary algorithms due to the exponentially increased search space and …
Deep Insights into Automated Optimization with Large Language Models and Evolutionary Algorithms
H Yu, J Liu - arxiv preprint arxiv:2410.20848, 2024 - arxiv.org
Designing optimization approaches, whether heuristic or meta-heuristic, usually demands
extensive manual intervention and has difficulty generalizing across diverse problem …
extensive manual intervention and has difficulty generalizing across diverse problem …
Artificial evolutionary intelligence (AEI): evolutionary computation evolves with large language models
Deep learning (DL) and evolutionary computation (EC), two main branches of artificial
intelligence, have attracted attention in a far different way over the past decades. On the one …
intelligence, have attracted attention in a far different way over the past decades. On the one …
Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons
In the evolutionary computing community, the remarkable language-handling capabilities
and reasoning power of large language models (LLMs) have significantly enhanced the …
and reasoning power of large language models (LLMs) have significantly enhanced the …
MOLLM: Multi-Objective Large Language Model for Molecular Design--Optimizing with Experts
Molecular design plays a critical role in advancing fields such as drug discovery, materials
science, and chemical engineering. This work introduces the Multi-Objective Large …
science, and chemical engineering. This work introduces the Multi-Objective Large …
An Evolutionary Large Language Model for Hallucination Mitigation
The emergence of LLMs, like ChatGPT and Gemini, has marked the modern era of artificial
intelligence applications characterized by high-impact applications generating text, images …
intelligence applications characterized by high-impact applications generating text, images …