FOSC-X uses bounded dynamic programming to compute top-M optimal non-horizontal cuts from clustering hierarchies in linear time, with or without cluster-count constraints.
J Mach Learn Res 7:1–30, https://dl.acm.org/doi/10.5555/1248547.1248548
2 Pith papers cite this work. Polarity classification is still indexing.
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LLaMA 3.1 extracts visual rating scores from Dutch neuroradiology reports with 87-96% balanced accuracy but only 66-80% on numerical counts, with few-shot prompting raising the latter to 81-92%.
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FOSC-X: An Extended Framework for Optimal Local Cuts and Non-Horizontal Cluster Selection from Clustering Hierarchies
FOSC-X uses bounded dynamic programming to compute top-M optimal non-horizontal cuts from clustering hierarchies in linear time, with or without cluster-count constraints.
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Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model
LLaMA 3.1 extracts visual rating scores from Dutch neuroradiology reports with 87-96% balanced accuracy but only 66-80% on numerical counts, with few-shot prompting raising the latter to 81-92%.