4 papers
Attention-Only White-Box Transformer via LeJEPA-Based Self-Supervised Pretraining
Yang Bai, Linyuan Wang, Haoyang Jiang +3
Existing studies on self-supervised learning for white-box networks typically decouple the derivation of white-box networks via optimization algorithms from self-supervised learnin…
A Quantization-Aware Training Based Lightweight Method for Neural Distinguishers
Guangwei Xiong, Linyuan Wang, Zhizhong Zheng +2
In 2019, Gohr pioneered the application of deep neural networks to differential cryptanalysis, developing DNN-based neural distinguisher classifiers to analyze the SPECK lightweigh…
Interpretable and Sparse Linear Attention with Decoupled Membership-Subspace Modeling via MCR2 Objective
Tianyuan Liu, Libin Hou, Linyuan Wang +1
Maximal Coding Rate Reduction (MCR2)-driven white-box transformer, grounded in structured representation learning, unifies interpretability and efficiency, providing a reliable whi…
Dense Optimizer : An Information Entropy-Guided Structural Search Method for Dense-like Neural Network Design
Liu Tianyuan, Hou Libin, Wang Linyuan +2
Dense Convolutional Network has been continuously refined to adopt a highly efficient and compact architecture, owing to its lightweight and efficient structure. However, the curre…