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 13
In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization
Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation under limited evaluation budgets, leading to…Rethinking Pairwise Token Interaction in Spiking Transformers
Spiking Transformers inherit token interaction mechanisms from conventional Transformers, yet their sparse binary representations fundamentally alter how token-to-token communication is established.When Recursive Models Finish Computing
Recursive models can continue updating their latent states beyond their nominal inference budget, so an incorrect output at that budget does not show whether computation is unfinished or has entered…NeuroRule: Making Black-Box Neural Networks Explainable through Rule-set Evolution
High-capacity neural network models have achieved state-of-the-art performance across diverse classification tasks, yet they frequently operate as black-box models, lacking the transparency…The Computational Value of Sensory-Aligned Receptive Fields Depends on Neuronal Expressivity
Biological sensory neurons have selective receptive fields organized along meaningful stimulus coordinates, such as frequency, motion direction, or retinotopic position.LexLattice: Multilingual Extractive Summarization via Neural Cellular Automata on Document Hierarchies
Faithfulness is a central concern in legal text summarization, which motivates extractive approaches that select verbatim content traceable to its source.LukeNet: A lightweight CNN integrated with an XAI model for Smart acute lymphoblastic leukemia detection and management
Acute Lymphoblastic Leukemia (ALL) patients require early, accurate detection to enable timely treatment and effective patient management.Genetic Programming with Behaviour-based Niching for Learning Guided Local Search in Vehicle Routing Problems
Genetic Programming Guided Local Search (GPGLS) learns utility functions that guide local search for vehicle routing.DCL-GPGLS: Dynamic Curriculum Learning for Genetic Programming Guided Local Search in Large-Scale Vehicle Routing
Genetic Programming Guided Local Search (GPGLS) uses genetic programming to evolve utility functions for guided local search in large-scale vehicle routing problems (LSVRPs).QLoRA Fine-Tuning of Ministral LLM for Sequence-to-Function Protein Annotation
Functional annotation of newly sequenced proteins remains a bottleneck in molecular biology: the number of sequences in public repositories grows far faster than the capacity for manual curation.Harness-Zero: Harness Distillation via Agent-as-Harness
Agent harnesses, the external systems that mediate model-environment interaction, can substantially improve agent performance, but their gains remain tied to the harness at deployment.Online Automated Algorithm Design with Large Language Models
Large language models (LLMs) enable automated algorithm design (AAD) through reasoning and code synthesis.Universal Fractal Natural Language Decision Map: Real-Time Edge Triage Across Heterogeneous Domains
Deploying Large Language Models for runtime operational triage incurs prohibitive latency (>100-500 ms), high VRAM requirements (>4-8 GB), and excessive energy dissipation.Sensing to Intelligence: Principles for Neuromorphic Circuits and Systems
Neuromorphic engineering began with the idea that the physical behavior of a system could itself be used for computation, taking inspiration from the way nervous systems sense, adapt, and evolve in…LPINNs: First-Layer Gated Localization for Physics-Informed Neural Networks
Physics-informed neural networks (PINNs) use one shared representation over the computational domain, which can become difficult to optimize on long domains and for high-order operators.Adaptive Differential Evolution and Multistart Search for Noisy QAOA Optimization
We benchmark classical optimization of a fixed low-depth Quantum Approximate Optimization Algorithm (QAOA) ansatz across four cost-Hamiltonian families at $N=12$, $p=3$, and $D=6$.Emergent Intelligence: Resonant Oscillators Produce Proactive Adaptive Behavior
Most artificial neural systems are built to map given inputs to outputs.A Confidence-Driven Evolutionary Algorithm for Noisy Optimization with Joint Chance Constraints
Many real-world optimization problems involve noisy objective evaluations and probabilistic constraints, particularly in the form of joint chance constraints, which are computationally expensive to…Predictive Suppression Layers for Communication-Efficient Spiking Neural Networks
Feedforward Spiking Neural Networks (SNNs) typically propagate every generated spike indiscriminately, disregarding whether the information is redundant from an information-theoretic perspective.Trust-Aware Output Management for Physical Neural Network in Cloud-Continuum Systems
Physical Neural Networks (PNNs) introduce new opportunities for cloud continuum computing, but their outputs may be affected by noise, drift, delay, and incomplete reliability information.