arXiv cs.LG
· Papers
LiST: Lipschitz Scaling Training for Robust and Calibrated Neural Networks
arXiv:2607.07745v1 Announce Type: new Abstract: While accuracy, robustness, and calibration are all essential for reliable neural networks, they are often studied separately; developing models that satisfy all three simultaneously remains a central challenge. Lipschitz-constrained models guarantee robustness by design,