The bidirectional interaction between large Language Models and Evolutionary Computation is reviewed and how their complementary strengths can be leveraged in hybrid intelligent systems is examined.
This work splits each flagged answer into individual factual claims, checks each against the retrieved source, and compares leaving the answer untouched with three repair strategies of increasing richness: deleting an unsupported claim, replacing it with source text, and rewriting it.
Sai Krishna Reddy Mulakkayala, Niki van Stein, A. Plaat· 0 citations
This work introduces a suite of synthetic multi-objective test problems with analytically controlled Pareto fronts and deliberately uninformative objective values, designed to decouple algorithmic behaviour from problem structure, allowing bias induced purely by algorithmic operators and design choices to be observed.
Jakub Kůdela, Niki van Stein, T. Bäck et al.· Annual Conference on Genetic...· 0 citations
This thesis contributes a methodology for evaluating prompt operators through isolated parent-child comparisons, enabling their behaviour to be characterized independently of complete evolutionary runs.
Opleiding Informatica, Niki van Stein, Anna V. Kononova· 0 citations
This work presents LACE, an AutoML framework that instead searches over complete executable pipeline programs: an evolutionary loop maintains a population of scikit-learn-compatible Python classes, and a large language model acts as the variation operator.
Sofoklis Kitharidis, C. Veenman, J. V. van Rijn et al.· 0 citations
This work proposes an automated framework that generates and refines benchmark suites using large language models (LLMs) and evolutionary search and shows that this combined approach substantially increases discriminability, improving scores from approximately 2.04 to 2.58.
Ananta Shahane, Niki van Stein· GECCO Companion· 0 citations
EvoHIIT, an LLM-assisted evolutionary framework for the design of High-Intensity Interval Training (HIIT) programs, is introduced, and preference-based selection mechanisms are studied to provide empirical insight into human-aligned evolution of natural language solutions.
Johana Chen, Niki van Stein, Robert Cabri et al.· Proceedings of the Genetic a...· 0 citations
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