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🏛️ The Neural & Evolutionary Crypt
cs.NE: Where Neural & Evolutionary papers rest without their code.
6370
Total Papers
5604
No Code
153
Twilight
613
Has Code
9.6%
Survival Rate
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Attention via Synaptic Plasticity is All You Need: A Biologically Inspired Spiking Neuromorphic Transformer
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Towards a Comprehensive Theory of Reservoir Computing
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DS-ATGO: Dual-Stage Synergistic Learning via Forward Adaptive Threshold and Backward Gradient Optimization for Spiking Neural Networks
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ToxSearch: Evolving Prompts for Toxicity Search in Large Language Models
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Benchmarking that Matters: Rethinking Benchmarking for Practical Impact
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Phase-Coded Memory and Morphological Resonance: A Next-Generation Retrieval-Augmented Generator Architecture
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An improved clustering-based multi-swarm PSO using local diversification and topology information
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Temporal-adaptive Weight Quantization for Spiking Neural Networks
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MECHBench: A Set of Black-Box Optimization Benchmarks originated from Structural Mechanics
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Dynamic Weight Adaptation in Spiking Neural Networks Inspired by Biological Homeostasis
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On the Structural and Statistical Flaws of the Exponential-Trigonometric Optimizer
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Further Commentary on the Sooty Tern Optimization Algorithm and Tunicate Swarm Algorithm
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Spatio-Temporal Cluster-Triggered Encoding for Spiking Neural Networks
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Understanding Electro-communication and Electro-sensing in Weakly Electric Fish using Multi-Agent Deep Reinforcement Learning
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Bi-Objective Evolutionary Optimization for Large-Scale Open Pit Mine Scheduling Problem under Uncertainty with Chance Constraints
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Gate-level boolean evolutionary geometric attention neural networks
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Improved Runtime Guarantees for the SPEA2 Multi-Objective Optimizer
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Towards a Rigorous Understanding of the Population Dynamics of the NSGA-III: Tight Runtime Bounds
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From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
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Evo* 2025 -- Late-Breaking Abstracts Volume
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Uncertainty-Aware Dual-Ranking Strategy for Offline Data-Driven Multi-Objective Optimization
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Fractional Artificial Neural Networks for Growth Models
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