Yingtao Zhang

Cannistraci-Hebb Training on Ultra-Sparse Spiking Neural Networks

Alignment-Enhanced Integration of Connectivity and Spectral Sparsity in Dynamic Sparse Training of LLM

From Transformer to Transponder: Introducing Contextual Modulation Training for Residual Learning in LLMs

A Dendritic-Inspired Network Science Generative Model for Topological Initialization of Connectivity in Sparse Artificial Neural Networks

Network Shape Automata: a brain network inspired collaborative filter for link prediction in bipartite complex networks and recommendation systems

Brain network science modelling of sparse neural networks enables Transformers and LLMs to perform as fully connected

Adaptive Cannistraci-Hebb Network Automata Modelling of Complex Networks for Path-based Link Prediction

Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks

Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models

Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks