2 papers
cs.LG2026
Quantifying Depth Sufficiency in Residual Neural Networks: A First-Order Criterion
Zeyu Liu, Jinhao Zhang, Yunquan Zhang +4
How can we determine whether a trained neural network is already deep enough? We study this under a fixed function-preserving residual-growth protocol specifying insertion location…
cs.LG2026
Mechanisms of Width Scaling in Normalized Residual Networks: The Effective Alignment Dimension
Jinhao Zhang, Zeyu Liu, Zicheng Yan +4
Existing theories of neural-network width characterize asymptotic limits, but provide limited guidance on whether an expansion direction identified from finite training data remain…