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cs.LG2026
Neural Networks Provably Learn Spectral Representations for Group Composition
Jianliang He, Leda Wang, Fengzhuo Zhang +2
Understanding how structured internal structure emerges during neural network training is central to the study of deep learning. We investigate this phenomenon through the group co…
cs.LG2026
On the Mechanism and Dynamics of Modular Addition: Fourier Features, Lottery Ticket, and Grokking
Jianliang He, Leda Wang, Siyu Chen +1
We present a comprehensive analysis of how two-layer neural networks learn features to solve the modular addition task. Our work provides a full mechanistic interpretation of the l…
cs.LG2025
Understanding and Enhancing Mask-Based Pretraining towards Universal Representations
Mingze Dong, Leda Wang, Yuval Kluger
Mask-based pretraining has become a cornerstone of modern large-scale models across language, vision, and recently biology. Despite its empirical success, its role and limits in le…