Lsys encoding excels in neural network evolution, achieving a food count of 3802, surpassing Matrix encoding.

Alexander Stuy, Nodin Weddington

MARS model achieves 21x training speedup and significant performance improvement through parallelization and subtractive skip connections.

Coşku Can Horuz, Andrea Ceni, Claudio Gallicchio et al.

Similarity-based portfolio construction enhances black-box optimization via k-nearest neighbor fine-tuning.

Catalin-Viorel Dinu, Diederick Vermetten, Carola Doerr

Combining convolution and delay learning in RSNNs achieves 52x inference speedup and 99% parameter savings on audio tasks.

Lúcio Folly Sanches Zebendo, Eleonora Cicciarella, Michele Rossi

Neuromorphic parameter estimation for power converter health monitoring using spiking neural networks, achieving ~270x energy reduction.

Hyeongmeen Baik, Hamed Poursiami, Maryam Parsa et al.

Simulating mouse cortical neurogenesis generates a minimal circuit of 85 neurons, achieving over 90% accuracy on MNIST after one training epoch.

Duan Zhou

The cHM algorithm is a universal framework for continuous optimization, excelling on 28 benchmark functions.

Piotr A. Kowalski, Szymon Kucharczyk, Jacek Mańdziuk

LLMs as semantic interfaces and ethical mediators in neuro-digital ecosystems, introducing Neuro-Linguistic Integration.

Alexander V. Shenderuk-Zhidkov, Alexander E. Hramov

A synthesizable RTL architecture for predictive coding networks, supporting local prediction-error dynamics, executed directly in hardware.

Timothy Oh

Utilizing a Quadratic Surrogate Attractor to enhance Particle Swarm Optimization's global convergence and robustness.

Maurizio Clemente, Marcello Canova

Federated few-shot learning on neuromorphic hardware using FedUnion strategy achieves 77.0% accuracy.

Steven Motta, Gioele Nanni

Proposed an SRAM-based CIM accelerator optimizing linear-decay SNNs, achieving 15.9 to 69 times energy efficiency improvement.

Hongyang Shang, Shuai Dong, Yahan Yang et al.

Stable Spike achieves dual consistency optimization via bitwise AND operations, enhancing SNN recognition performance under ultra-low latency by up to 8.33%.

Yongqi Ding, Kunshan Yang, Linze Li et al.

This paper presents an event-driven E-Skin system with dynamic binary scanning and real-time SNN classification, achieving a 12.8x scan reduction and 92.11% accuracy.

Gaishan Li, Zhengnan Fu, Anubhab Tripathi et al.

Introduced NEMO-DE and NEEF-DE evolutionary frameworks for near-field multi-source localization, avoiding grid mismatch errors.

Seyed Jalaleddin Mousavirad, Parisa Ramezani, Mattias O'Nils et al.

Introduces ToxSearch-S with unsupervised speciation, boosting peak toxicity to 0.73 and semantic diversity, outperforming baseline in adversarial prompt search.

Onkar Shelar, Travis Desell

TEFormer enhances spiking Transformers with bidirectional temporal fusion, achieving superior performance across datasets.

Sicheng Shen, Mingyang Lv, Bing Han et al.

Lehmer code enhances permutation search efficiency; theoretical bounds and empirical tests confirm its advantage over classical encodings.

Yuxuan Ma, Valentino Santucci, Carsten Witt

AlphaEvolve combines LLM and automated evaluation in evolutionary search, discovering novel mathematical constructions across 67 problems, often surpassing known solutions.

Bogdan Georgiev, Javier Gómez-Serrano, Terence Tao et al.

SpikePool uses pooling attention for event-driven spiking transformers, reducing training time by 42.5% and inference time by 32.8%.

Donghyun Lee, Alex Sima, Yuhang Li et al.