Introducing neurotransmitter-inspired modulation in ANNs to enhance adaptability and stability.

Yupei Li, Manuel Milling, Berrak Sisman et al.

Study finds lineage isolation, not masking, is key for memory retention, improving AUC by 0.010.

Jia Huang, Yangjun Ou

Proposed a TTFS-based SNN architecture, scaling to 1.5 billion parameters in LLMs, significantly enhancing energy efficiency.

Zhuoya Zhao, Parsa Omidi, Aref Jafari et al.

Genetic algorithms enable tractable Bayesian network fusion by pre-fusion edge pruning, enhancing inference efficiency.

Pablo Torrijos, José A. Gámez, José M. Puerta et al.

GPU-accelerated tree-based genetic programming for symbolic regression constant optimization, achieving 9.9x throughput improvement.

Hao Mao, Xu Tony Liu, Shuai Lu et al.

MFSPNet uses model-free surrogate and PSO to optimize CNN architectures, achieving 3.91% error on CIFAR-10.

Asif Ameer, Maryam Bashir, Irfan Younas et al.

Introduces EMR-HyperNEAT, a tensorized batch approach for multi-resolution substrate discovery, achieving 12-34× GPU speedup at depth 6.

Romain Claret, Michael O'Neill, Paul Cotofrei et al.

Using ANTShapes simulated datasets, combined with convolutional SNNs, for event-based object classification, validating data quality and robustness.

M. Middleton, H. Kayan, B. Sen Bhattacharya et al.

SPEA-2-based multi-objective algorithm improves bug localization accuracy to 88.5%.

Waleed Ahmad, Mehtab Kiran Suddle, Maryam Bashir

Using eigenvector analysis, the paper proves more hypercube corners can be programmed as stable states, enhancing storage capacity.

Garimella Rama Murthy

Introduces a reinforcement learning-based decision confidence model for social credibility, revealing non-monotonic effects on group consensus and error propagation.

Gabriel Bontemps, Abhishek Banerjee

Introduces LLM-SPICEMixer with IGEL, boosting circuit synthesis rewards by 8.4%.

Stefan Uhlich, Yağız Gençer, Andrea Bonetti et al.

Analyzes multiple fixed points in discrete hysteresis neural networks; introduces entropy to control basin size distribution.

Yuta Arai, Seigo Nakamura, Ryoga Nakamura et al.

Proposes Petri net-based neural circuit model with formal timing guarantees, validated on feedback, lateral inhibition, and hierarchical feature detection microcircuits.

Carlo daCunha, Rodrigo Pena, Marcos Turqueti

Proposes a taxonomy of neural models based on state dynamics, credit assignment, and biological grounding, highlighting the disconnection between forward computation and learning mechanisms.

Hadi Al Mubasher, Mariette Awad

Introducing a analytical grid cell model combined with boundary vector cells reduces spatial aliasing by 94-99%, validated across three environments.

Alexander Johnson, Obadah Ghizawi, Ali A. Minai

Lapis employs First-Spike Latency and membrane leakage to realize Laplacian attention, achieving 96.56% accuracy on CIFAR-10 with 14.5× energy reduction.

Kaiwen Tang, Jiaqi Zheng, Zixuan Zhu et al.

This paper introduces a GNN-guided genetic algorithm for supply chain optimization under cost uncertainty, significantly improving initial solution quality and robustness.

Faezeh Ardali, Gerald M. Knapp

ASP uses membrane potential as a Bayesian belief, enabling adaptive region selection for 3D point cloud recognition, achieving 90.62% accuracy with linear energy savings.

Akarsh Jain, Arya Pawa, Ayush Debnath et al.

MOSAIC employs adversarial co-evolution with structure-based feature grids, significantly improving heuristic performance for combinatorial optimization problems.

Oguzhan Gungordu, Siheng Xiong, Faramarz Fekri