Adaptive Diffusion in Graph Neural Networks. - Jialin Zhao 004; Yuxiao Dong; Ming Ding 004; Evgeny Kharlamov; Jie Tang 001 (NeurIPS, 2021)

Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning. - Yingtao Zhang; Jialin Zhao 004; Wenjing Wu; Alessandro Muscoloni; Carlo Vittorio Cannistraci (ICLR, 2024)

Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models. - Yingtao Zhang; Haoli Bai; Haokun Lin; Jialin Zhao 004; Lu Hou 002; Carlo Vittorio Cannistraci (ICLR, 2024)

Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks. - Jialin Zhao 004; Yingtao Zhang; Xinghang Li; Huaping Liu; Carlo Vittorio Cannistraci (CoRR, 2024)

Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models. - Jialin Zhao 004; Yingtao Zhang; Carlo Vittorio Cannistraci (CoRR, 2025)

Brain-inspired sparse training enables Transformers and LLMs to perform as fully connected. - Yingtao Zhang; Jialin Zhao 004; Wenjing Wu; Ziheng Liao; Umberto Michieli; Carlo Vittorio Cannistraci (CoRR, 2025)