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cs.LG2026
Predicting Out-of-Distribution Generalization of Neural Operators via Observable Spectral Error Decomposition
Hang-Cheng Dong, Pengcheng Cheng
Neural operators have emerged as powerful surrogates for solving partial differential equations (PDEs), yet their reliability under distribution shift remains a critical barrier to…
cs.LG2026
Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models
Jing-Xiao Liao, Tianwei Zhang, Yu-Hao Jiang +3
The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from the concept of "enlightenment…
cs.LG2026
Quotient Geometry, Effective Curvature, and Implicit Bias in Simple Shallow Neural Networks
Hang-Cheng Dong, Pengcheng Cheng
Overparameterized shallow neural networks admit substantial parameter redundancy: distinct parameter vectors may represent the same predictor due to hidden-unit permutations, resca…