4 papers
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…
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…