AI & Machine Learning · Computer Science & AI
Neural & Evolutionary Computing
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324 papers, from 4 September 2026 to 5 November 2026: 324 arXiv preprints.
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Newest papers, page 16
GeoTrussRover: Morphological Computation with Contact-Semantic Control Primitives
Reconfigurable robots can change their contact geometry when a fixed body cannot negotiate an obstacle.Breaking the Central Bias: Spatially Partitioned Experts for Coordinate-Based Neuroevolution
Evolvable-Substrate HyperNEAT (ES-HyperNEAT), a bio-inspired indirect encoding that determines neuron placement and connection weights from spatial coordinates, exhibits a failure mode on MNIST as a…Predicting Privacy Leakage from Weight Spectral Density
Membership inference attacks (MIAs) are widely used to audit the privacy disclosure risk of machine learning models, however current state-of-the-art attacks require training computationally…T-GADE: Thermodynamical Generative-AI-Driven Evolution of LLM Artifacts
Integrating evolutionary computation and large language models (LLMs) requires control of population diversity as well as generative capability.Feasibility and Memory Mechanisms of Chern-Simons Context Reservoir Computation
We investigate whether a Chern-Simons (CS) context reservoir is a viable computational substrate and whether evolving its gauge connection provides a benefit beyond simpler mechanisms.Robust Industrial Cyber Physical Classification Using Neuromorphic Temporal Embeddings and Hybrid SNN XGBoost Under Machine Unlearning Attacks
The digitalisation of electrical distribution networks has increased the exposure of power-grid infrastructure to cyber attacks.Teacher Geometry Shapes Learnability in Teacher-Student Networks
Teacher-student systems, in which a teacher neural network generates training labels so that a student neural network can learn to implement the same function, are widely used as an abstract setting…A Bio-Plausible Visual Neural Network for Locust-Inspired Collision Perception
Locust visual systems have long served as an important biological paradigm for studying looming perception and collision avoidance.Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms
This paper introduces an evolutionary computation approach for consensus in structural Bayesian Network (BN) fusion under the constraint of limited treewidth.Training Trajectories Determine Circuit Removability in Annealable Soft-Prior Transformers
Soft positional priors can help small Transformers learn retrieval circuits, but it is unclear whether the resulting circuits remain functional once the prior is removed.Fractional-order hardware for neuromorphic computing: Is the order really the problem?
Does a neuromorphic system need a true power-law memory kernel, and if so, can anyone build one?A Gradient-based yet Spike-Timing-Dependent Solution to the Feedback Learning Problem in Neural Microcircuits
The brain uses discrete spikes for dynamic computation, yet, how neural microcircuits (NMCs) solve temporal credit assignment using local spike timing remains a fundamental open question.Why shared attention vectors fail: a case for outcome-indexed tuning
Dimensional attention in learning is often implemented as a globally shared attention vector, where each stimulus dimension corresponds to a single scalar.Gradland: On Phenomenal Experience, Differentiated Across Many Dimensions
This paper investigates the hypothesis that the first-order structure of physical interactions, i.e. gradients or Jacobians, characterizes the structure of phenomenal experience.Photonic reservoir computing with dimensionally compressed readout
This work addresses a hardware constraint in reservoir computing: the limited size of the readout layer imposed by systems with a physical readout.Emergent Charging Coordination in Electric Delivery Fleets
In electric delivery fleets, mid-shift charging is non-trivial: each vehicle must decide when, where and how much to charge to finish on time with battery above a safety floor.Linear Algebra Foundations of Efficient Attention: A Phase Reversal in Rank Collapse Under SVD Compression
Linear algebra provides the framework of concepts (matrix rank, singular value decomposition (SVD), and eigendecomposition) that modern artificial intelligence employs to encode, compress, and…Formation of structural attractors in neuromorphic systems
This paper examines the theory of Invariant Structural Learning (ISL), which proposes a non-optimization approach to concept formation.Threshold-Based Selection for Continuous Optimization: A Leaf-Abscission Instantiation
This paper formalizes threshold-based selection as an evaluation-gating architecture in which each incumbent is tested before variation and a replacement is generated and evaluated only when…Minimizing the Effect of Sleep Deprivation in the Forward-Forward Algorithm
This paper addresses the challenge posed by sleep deprivation in the Forward-Forward algorithm, where separating the two passes in this algorithm and imbalancing the data processing in the passes is…