LiBaGS scores and selects synthetic data near decision boundaries using proximity, uncertainty, density, and validity, with boundary-gap allocation and marginal stopping to improve training accuracy.
Nearest neighbor pattern classification.IEEE transactions on information theory, 13(1):21–27
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Sheet as Token represents each worksheet as a single dense token and uses a multi-channel graph retriever to improve retrieval of supporting sheets in multi-sheet workbooks.
A small set of policy-influential scientists dominate citations in IGO documents through tight international co-authorship networks and fast policy uptake, with concentration varying by field.
citing papers explorer
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LiBaGS: Lightweight Boundary Gap Synthesis for Targeted Synthetic Data Selection
LiBaGS scores and selects synthetic data near decision boundaries using proximity, uncertainty, density, and validity, with boundary-gap allocation and marginal stopping to improve training accuracy.
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Sheet as Token: A Graph-Enhanced Representation for Multi-Sheet Spreadsheet Understanding
Sheet as Token represents each worksheet as a single dense token and uses a multi-channel graph retriever to improve retrieval of supporting sheets in multi-sheet workbooks.
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Influential scientists shape knowledge flows between science and IGO policy
A small set of policy-influential scientists dominate citations in IGO documents through tight international co-authorship networks and fast policy uptake, with concentration varying by field.