8 papers
LLM-Driven Evolutionary Generation of Multi-Objective Bayesian Optimization Algorithms
Georgios Laskaris, Reuben Brasher, Niki van Stein +3
Designing effective multi-objective Bayesian optimization (MOBO) algorithms requires balancing many interdependent design choices whose optimal configuration is problem-dependent a…
3DMorph: Single-Image-Guided Local 3D Shape Editing and Morphing
Tobias Preintner, Yunfei Deng, Phillip Müller +5
Despite recent progress in 3D generation, intuitive editing of existing shapes remains limited. Unlike images, which benefit from well-established inpainting tools, general 3D obje…
MuViS: Multimodal Virtual Sensing Benchmark
Jens U. Brandt, Noah C. Puetz, Jobel Jose George +5
Virtual sensing aims to infer hard-to-measure quantities from accessible measurements and is central to perception and control in physical systems. Despite rapid progress from firs…
Investigating the Interplay of Parameterization and Optimizer in Gradient-Free Topology Optimization: A Cantilever Beam Case Study
Jelle Westra, Iván Olarte RodrÃguez, Niki van Stein +2
Gradient-free black-box optimization (BBO) is widely used in engineering design and provides a flexible framework for topology optimization (TO), enabling the discovery of high-per…
Benchmarking that Matters: Rethinking Benchmarking for Practical Impact
Anna V. Kononova, Niki van Stein, Olaf Mersmann +14
Benchmarking has driven scientific progress in Evolutionary Computation, yet current practices fall short of real-world needs. Widely used synthetic suites such as BBOB and CEC iso…
EvoCAD: Evolutionary CAD Code Generation with Vision Language Models
Tobias Preintner, Weixuan Yuan, Adrian König +3
Combining large language models with evolutionary computation algorithms represents a promising research direction leveraging the remarkable generative and in-context learning capa…