A curvature penalty for KANs, derived to respect compositional effects and equipped with a proven upper bound on full-model curvature, produces smoother activations while preserving accuracy.
Kolmogorov-Arnold Transformer
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
A new framework called ERR decomposes UHD image restoration into three frequency stages with specialized sub-networks and introduces the LSUHDIR benchmark dataset of over 82,000 images.
A new tensor framework for multi-layer decoupling of multivariate functions is proposed via ParaTuck decompositions and bilevel optimization.
citing papers explorer
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KANs need curvature: penalties for compositional smoothness
A curvature penalty for KANs, derived to respect compositional effects and equipped with a proven upper bound on full-model curvature, produces smoother activations while preserving accuracy.
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From Zero to Detail: A Progressive Spectral Decoupling Paradigm for UHD Image Restoration with New Benchmark
A new framework called ERR decomposes UHD image restoration into three frequency stages with specialized sub-networks and introduces the LSUHDIR benchmark dataset of over 82,000 images.
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Tensor-based Multi-layer Decoupling
A new tensor framework for multi-layer decoupling of multivariate functions is proposed via ParaTuck decompositions and bilevel optimization.