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Zhong-Xuan Liu

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#machine learning Preprint Sep 2026

Weighted Data Selection: Sharp Upper-Half and Five-Dimensional Laws

How much risk does a small reweighted training support retain? For finite weighted least squares with the minimum-norm learner, we prove the exact law $\Gamma_d(n)=3-n/d$ throughout $\lceil3d/2\rceil\leq n\leq2d-1$. The guarantee covers every observed feature rank and uses selections that preserve the full feature span...

Zhong-Xuan Liu, Hong-Zhi Wang · 0 citations
#natural language process... Preprint Sep 2026

Record Grouping Controls Evidence Weight in Language Models

Retrieved records are presentation units; a supplied partition determines which records enter a language model as one evidential contribution. We characterize the invariant group-content state that removes within-group copies while retaining complementary canonical content, show that equal group counts can encode diffe...

Zhong-Xuan Liu, Si-Cheng Zhou, Hong-Zhi Wang · 0 citations
#machine learning Preprint Sep 2026

Target-Independent Micro-Interventions for Predicting Training Response Across Language-Model Families

Benchmark scores describe what a checkpoint can do now, but they do not determine how it will respond to the next training episode. We measure this missing state by branching four short, standardized, target-independent micro-interventions from the same checkpoint and recording their effects in a common capability spac...

Zhong-Xuan Liu, Si-Cheng Zhou, Hong-Zhi Wang · 0 citations

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