Neural and Evolutionary Computing Papers

A Scalable Benchmark Test Suite for Dynamic Multi-Objective Optimization with a Changing Number of Objectives Ke Shang, Zhiyun Xiao, Yuxuan Liu, Jianguo Li, Shaojiang Wang, Wei Sun arxiv.org/abs/2605.25785 [𝚌𝚜.𝙽𝙴]

Anarchy in the swarm: Testing informed and uninformed diversity-enhancing mechanisms within PSO framework Piotr Urbańczyk, Aleksandra Urbańczyk arxiv.org/abs/2605.25093 [𝚌𝚜.𝙽𝙴 𝚖𝚊𝚝𝚑.𝙾𝙲]

Cultivating Machine Intelligence: The OMEGA Shift from Top-Down Optimization to Autopoietic Cognitive Ecologies Ata G. Zare arxiv.org/abs/2605.25062 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸]

UniSpike: Accelerating Spiking Neural Networks on Neuromorphic Systems via Eliminating Address Redundancy Qinghui Xing, Zhuo Chen, Xin Du, Ouwen Jin, Ming Zhang, … arxiv.org/abs/2605.23796 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝚁] 💬Accepted to the 63rd Design Automation Conference (DAC 2026)

SpikingMoE: SDPrompt-Guided Dynamic Expert Fusion in Spiking Neural Networks Yukai Yang, Chenxi Qin, Jungang Li, Xin Zhang, Wenwei Shao, Liqun Chen arxiv.org/abs/2605.23188 [𝚌𝚜.𝙽𝙴]

Quantum Genetic Optimization for Negative Selection Algorithms in Anomaly Detection Giancarlo P. Gamberi, Calebe P. Bianchini arxiv.org/abs/2605.22527 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙴𝚃]

Guiding Multi-Objective Genetic Programming with Description Length Improves Symbolic Regression Solutions Gabriel Kronberger, Fabricio Olivetti de Franca, Deaglan J. Bartlett, Harry Desmond, Pedro G. Ferreira arxiv.org/abs/2605.22374 [𝚌𝚜.𝙽𝙴 𝚜𝚝𝚊𝚝.𝙼𝙻]

Temporal Coding as a Substrate for Sensorimotor Object Inference: A Spiking Reinterpretation of Thousand Brains Architecture Joy Bose arxiv.org/abs/2605.22206 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸 𝚌𝚜.𝚁𝙾]

How to Build Marcus's Algebraic Mind: Algebro-Deterministic Substrate over Galois Fields Hiroyuki Chuma, Kanji Otsuk, Yoichi Sato arxiv.org/abs/2605.21379 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸]

Genetic Programming with Transformer-Based Mutation for Approximate Circuit Design Ondrej Galeta, Lukas Sekanina arxiv.org/abs/2605.21055 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙻𝙶]

Convergence Analysis of Evolution Strategies for Mixed-Integer Optimization Ryoki Hamano, Kento Uchida, Shinichi Shirakawa arxiv.org/abs/2605.21000 [𝚌𝚜.𝙽𝙴] 💬Accepted at Genetic and Evolutionary Computation Conference (GECCO '26)

Privacy-Preserving Distributed Optimization Under Time Constraints Using Secure Multi-Party Computation and Evolutionary Algorithms Sebastian Gruber, Tobias Harzfeld, Christoph G. Schuetz, Florian Wohner, Thomas Lorünser arxiv.org/abs/2605.20944 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙲𝚁]

E-ReCON: An Energy- and Resource-Efficient Precision-Configurable Sparse nvCIM Macro for Conventional and Spiking Neural Edge Inference Ankit Kumar Tenwar, Mukul Lokhande, Santosh Kumar Vishvakarma arxiv.org/abs/2605.20717 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝚁 𝚌𝚜.𝙲𝚅 𝚎𝚎𝚜𝚜.𝙸𝚅]

What Do Evolutionary Coding Agents Evolve? Nico Pelleriti, Sree Harsha Nelaturu, Zhanke Zhou, Zongze Li, Max Zimmer, Bo Han, Sebastian Pokutta arxiv.org/abs/2605.20086 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸 𝚌𝚜.𝙻𝙶]

Multi-population Diversity-guided Genetic Algorithm for Feature Selection in Network Intrusion Detection Chunzhen Li arxiv.org/abs/2605.19864 [𝚌𝚜.𝙽𝙴]

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization Xingyu Li arxiv.org/abs/2605.19119 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸 𝚌𝚜.𝙻𝙶]

Mapping the Fitness Landscape: A Structure-Guided Approach to Multi-Modal Optimization Meng Xiang, Pei Yan arxiv.org/abs/2605.18351 [𝚌𝚜.𝙽𝙴]

Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks Alessio Caviglia, Filippo Marostica, Alessandro Savino, Stefano Di Carlo arxiv.org/abs/2605.18003 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸]

Adaptive Stochastic Natural Gradient Method for Safe Optimization on Binary Space Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shinichi Shirakawa arxiv.org/abs/2605.17925 [𝚌𝚜.𝙽𝙴] 💬This paper has been accepted as a full paper at GECCO2026

Evolutionary Extreme Learning Machine of ab-initio Energy Landscapes for Crystal Structure Prediction using Manta Ray Optimization with Levy Flight Adrian Rubio-Solis arxiv.org/abs/2605.17148 [𝚌𝚜.𝙽𝙴 𝚌𝚜.𝙰𝙸 𝚌𝚜.𝙻𝙶]