Machine unlearning in brain-inspired neural network paradigms

C Wang, Z Ying, Z Pan - Frontiers in Neurorobotics, 2024 - frontiersin.org
Machine unlearning, which is crucial for data privacy and regulatory compliance, involves
the selective removal of specific information from a machine learning model. This study …

Developmental plasticity-inspired adaptive pruning for deep spiking and artificial neural networks

B Han, F Zhao, Y Zeng, G Shen - IEEE Transactions on Pattern …, 2024 - ieeexplore.ieee.org
Developmental plasticity plays a prominent role in sha** the brain's structure during
ongoing learning in response to dynamically changing environments. However, the existing …

Spatial-Temporal Spiking Feature Pruning in Spiking Transformer

Z Zhou, K Che, J Niu, M Yao, G Li… - … on Cognitive and …, 2024 - ieeexplore.ieee.org
Spiking Neural Networks (SNNs) are known for brain-inspired architecture and low power
consumption. Leveraging bio-compatibility and self-attention mechanism, Spiking …

MaskPrune: Mask-based LLM Pruning for Layer-wise Uniform Structures

J Qin, J Tan, K Zhang, X Cai, W Wang - arxiv preprint arxiv:2502.14008, 2025 - arxiv.org
The remarkable performance of large language models (LLMs) in various language tasks
has attracted considerable attention. However, the ever-increasing size of these models …

Criticality-Guided Efficient Pruning in Spiking Neural Networks Inspired by Critical Brain Hypothesis

S Chen, B Liu, H You - arxiv preprint arxiv:2311.16141, 2023 - arxiv.org
Spiking Neural Networks (SNNs) have gained considerable attention due to the energy-
efficient and multiplication-free characteristics. The continuous growth in scale of deep …