EMBER: Autonomous Cognitive Behaviour from Learned Spiking Neural Network Dynamics in a Hybrid LLM Architecture
Fuente:
arXiv
Saved in:
| Main Author: | Savage, William |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning with Spike Synchrony in Spiking Neural Networks
by: Tian, Yuchen, et al.
Published: (2025)
by: Tian, Yuchen, et al.
Published: (2025)
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2024)
by: Chakraborty, Biswadeep, et al.
Published: (2024)
A Hybrid Spiking-Convolutional Neural Network Approach for Advancing Machine Learning Models
by: Sanaullah, et al.
Published: (2024)
by: Sanaullah, et al.
Published: (2024)
Continual Learning with Columnar Spiking Neural Networks
by: Larionov, Denis, et al.
Published: (2025)
by: Larionov, Denis, et al.
Published: (2025)
CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
by: Huang, Yongsheng, et al.
Published: (2025)
by: Huang, Yongsheng, et al.
Published: (2025)
Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks
by: Han, Bing, et al.
Published: (2023)
by: Han, Bing, et al.
Published: (2023)
Learning in Spiking Neural Networks with a Calcium-based Hebbian Rule for Spike-timing-dependent Plasticity
by: Girão, Willian Soares, et al.
Published: (2025)
by: Girão, Willian Soares, et al.
Published: (2025)
Dynamic Weight Adaptation in Spiking Neural Networks Inspired by Biological Homeostasis
by: Zhou, Yunduo, et al.
Published: (2025)
by: Zhou, Yunduo, et al.
Published: (2025)
Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks
by: Saiin, Ryuji, et al.
Published: (2023)
by: Saiin, Ryuji, et al.
Published: (2023)
Beyond Rate Coding: Surrogate Gradients Enable Spike Timing Learning in Spiking Neural Networks
by: Yu, Ziqiao, et al.
Published: (2025)
by: Yu, Ziqiao, et al.
Published: (2025)
SpikeFI: A Fault Injection Framework for Spiking Neural Networks
by: Spyrou, Theofilos, et al.
Published: (2024)
by: Spyrou, Theofilos, et al.
Published: (2024)
Efficient Training of Spiking Neural Networks by Spike-aware Data Pruning
by: Ma, Chenxiang, et al.
Published: (2025)
by: Ma, Chenxiang, et al.
Published: (2025)
Neural Dynamics Self-Attention for Spiking Transformers
by: Zhang, Dehao, et al.
Published: (2026)
by: Zhang, Dehao, et al.
Published: (2026)
Optimization of Low-Latency Spiking Neural Networks Utilizing Historical Dynamics of Refractory Periods
by: Tao, Liying, et al.
Published: (2025)
by: Tao, Liying, et al.
Published: (2025)
Parallel Hyperparameter Optimization Of Spiking Neural Network
by: Firmin, Thomas, et al.
Published: (2024)
by: Firmin, Thomas, et al.
Published: (2024)
Stable Spike: Dual Consistency Optimization via Bitwise AND Operations for Spiking Neural Networks
by: Ding, Yongqi, et al.
Published: (2026)
by: Ding, Yongqi, et al.
Published: (2026)
SpikeExplorer: hardware-oriented Design Space Exploration for Spiking Neural Networks on FPGA
by: Padovano, Dario, et al.
Published: (2024)
by: Padovano, Dario, et al.
Published: (2024)
Towards Efficient Deep Spiking Neural Networks Construction with Spiking Activity based Pruning
by: Li, Yaxin, et al.
Published: (2024)
by: Li, Yaxin, et al.
Published: (2024)
SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks
by: Xu, Boxun, et al.
Published: (2025)
by: Xu, Boxun, et al.
Published: (2025)
Exploring the Limitations of Layer Synchronization in Spiking Neural Networks
by: Koopman, Roel, et al.
Published: (2024)
by: Koopman, Roel, et al.
Published: (2024)
Spiking Neural Networks: The Future of Brain-Inspired Computing
by: Aribe Jr, Sales G.
Published: (2025)
by: Aribe Jr, Sales G.
Published: (2025)
Learning Alzheimer's Disease Signatures by bridging EEG with Spiking Neural Networks and Biophysical Simulations
by: Mamoń, Szymon, et al.
Published: (2026)
by: Mamoń, Szymon, et al.
Published: (2026)
Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks
by: Wang, Lihao, et al.
Published: (2024)
by: Wang, Lihao, et al.
Published: (2024)
Reconstructing Spiking Neural Networks Using a Single Neuron with Autapses
by: Cai, Wuque, et al.
Published: (2026)
by: Cai, Wuque, et al.
Published: (2026)
Dynamic Spiking Framework for Graph Neural Networks
by: Yin, Nan, et al.
Published: (2023)
by: Yin, Nan, et al.
Published: (2023)
Generalization Bounds of Spiking Neural Networks via Rademacher Complexity
by: Zhang, Shao-Qun, et al.
Published: (2026)
by: Zhang, Shao-Qun, et al.
Published: (2026)
Input-Triggered Hardware Trojan Attack on Spiking Neural Networks
by: Raptis, Spyridon, et al.
Published: (2025)
by: Raptis, Spyridon, et al.
Published: (2025)
Temporal Regularization Training: Unleashing the Potential of Spiking Neural Networks
by: Zhang, Boxuan, et al.
Published: (2025)
by: Zhang, Boxuan, et al.
Published: (2025)
Spikingformer: A Key Foundation Model for Spiking Neural Networks
by: Zhou, Chenlin, et al.
Published: (2023)
by: Zhou, Chenlin, et al.
Published: (2023)
Evolving Efficient Genetic Encoding for Deep Spiking Neural Networks
by: Pan, Wenxuan, et al.
Published: (2024)
by: Pan, Wenxuan, et al.
Published: (2024)
TS-SNN: Temporal Shift Module for Spiking Neural Networks
by: Yu, Kairong, et al.
Published: (2025)
by: Yu, Kairong, et al.
Published: (2025)
NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework
by: Caviglia, Alessio, et al.
Published: (2026)
by: Caviglia, Alessio, et al.
Published: (2026)
An Introductory Review of Spiking Neural Network and Artificial Neural Network: From Biological Intelligence to Artificial Intelligence
by: Zheng, Shengjie, et al.
Published: (2022)
by: Zheng, Shengjie, et al.
Published: (2022)
Mamba-Spike: Enhancing the Mamba Architecture with a Spiking Front-End for Efficient Temporal Data Processing
by: Qin, Jiahao, et al.
Published: (2024)
by: Qin, Jiahao, et al.
Published: (2024)
A Study of Hybrid and Evolutionary Metaheuristics for Single Hidden Layer Feedforward Neural Network Architecture
by: Kashyap, Gautam Siddharth, et al.
Published: (2025)
by: Kashyap, Gautam Siddharth, et al.
Published: (2025)
Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks
by: Caviglia, Alessio, et al.
Published: (2026)
by: Caviglia, Alessio, et al.
Published: (2026)
NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning
by: Gautam, Ashish, et al.
Published: (2025)
by: Gautam, Ashish, et al.
Published: (2025)
Multi-compartment Neuron and Population Encoding Powered Spiking Neural Network for Deep Distributional Reinforcement Learning
by: Sun, Yinqian, et al.
Published: (2023)
by: Sun, Yinqian, et al.
Published: (2023)
Ecological Neural Architecture Search
by: Winter, Benjamin David, et al.
Published: (2025)
by: Winter, Benjamin David, et al.
Published: (2025)
A Scalable Hybrid Training Approach for Recurrent Spiking Neural Networks
by: Baronig, Maximilian, et al.
Published: (2025)
by: Baronig, Maximilian, et al.
Published: (2025)
Similar Items
-
Learning with Spike Synchrony in Spiking Neural Networks
by: Tian, Yuchen, et al.
Published: (2025) -
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2024) -
A Hybrid Spiking-Convolutional Neural Network Approach for Advancing Machine Learning Models
by: Sanaullah, et al.
Published: (2024) -
Continual Learning with Columnar Spiking Neural Networks
by: Larionov, Denis, et al.
Published: (2025) -
CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
by: Huang, Yongsheng, et al.
Published: (2025)