6 papers
GEAKG: Generative Executable Algorithm Knowledge Graphs
Camilo Chacón Sartori, José H. GarcÃa, Andrei Voicu Tomut +1
In the context of algorithms for problem solving, procedural knowledge -- the know-how of algorithm design and operator composition -- remains implicit in code, lost between runs,…
irace-evo: Automatic Algorithm Configuration Extended With LLM-Based Code Evolution
Camilo Chacón Sartori, Christian Blum
Automatic algorithm configuration tools such as irace efficiently tune parameter values but leave algorithmic code unchanged. This paper introduces a first version of irace-evo, an…
Combinatorial Optimization for All: Using LLMs to Aid Non-Experts in Improving Optimization Algorithms
Camilo Chacón Sartori, Christian Blum
Large Language Models (LLMs) have shown notable potential in code generation for optimization algorithms, unlocking exciting new opportunities. This paper examines how LLMs, rather…
Improving Existing Optimization Algorithms with LLMs
Camilo Chacón Sartori, Christian Blum
The integration of Large Language Models (LLMs) into optimization has created a powerful synergy, opening exciting research opportunities. This paper investigates how LLMs can enha…
Metaheuristics and Large Language Models Join Forces: Toward an Integrated Optimization Approach
Camilo Chacón Sartori, Christian Blum, Filippo Bistaffa +1
Since the rise of Large Language Models (LLMs) a couple of years ago, researchers in metaheuristics (MHs) have wondered how to use their power in a beneficial way within their algo…
VisGraphVar: A Benchmark Generator for Assessing Variability in Graph Analysis Using Large Vision-Language Models
Camilo Chacón Sartori, Christian Blum, Filippo Bistaffa
The fast advancement of Large Vision-Language Models (LVLMs) has shown immense potential. These models are increasingly capable of tackling abstract visual tasks. Geometric structu…