ToxSearch-S applies unsupervised speciation to evolutionary prompt search, maintaining capacity-limited species with exemplar leaders and species-aware selection to achieve higher peak toxicity and broader semantic coverage than standard methods.
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The paper reports 21 previously unknown variable stars in M71 along with refined cluster parameters (age 12.9 Gyr, [Fe/H] = -0.88, E(B-V) = 0.21, distance modulus 13.01) from a decontaminated CMD.
FASC is a dynamical systems clustering framework that decouples similarity measurement from optimization to deliver deterministic, order-independent results with linear scaling on 25 million aerosol mass spectra.
Optimizes ImageNet-pretrained AlexNet, UMAP, and a bagging multi-cluster voting scheme with K-means, Birch and Agg for unsupervised galaxy morphology classification, reporting improved stability and consistency with galaxy evolution expectations.
citing papers explorer
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Diversifying Toxicity Search in Large Language Models Through Speciation
ToxSearch-S applies unsupervised speciation to evolutionary prompt search, maintaining capacity-limited species with exemplar leaders and species-aware selection to achieve higher peak toxicity and broader semantic coverage than standard methods.
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Variable stars in the field of the Galactic globular cluster M71
The paper reports 21 previously unknown variable stars in M71 along with refined cluster parameters (age 12.9 Gyr, [Fe/H] = -0.88, E(B-V) = 0.21, distance modulus 13.01) from a decontaminated CMD.
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A Flexible Adaptive Stable Clustering Algorithm for Archive-Scale Online Mass Spectrometry
FASC is a dynamical systems clustering framework that decouples similarity measurement from optimization to deliver deterministic, order-independent results with linear scaling on 25 million aerosol mass spectra.
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Robustness Analysis of USmorph: II. Optimizing Feature Extraction, Dimensionality Reduction, and Clustering for Unsupervised Galaxy Morphology Classification
Optimizes ImageNet-pretrained AlexNet, UMAP, and a bagging multi-cluster voting scheme with K-means, Birch and Agg for unsupervised galaxy morphology classification, reporting improved stability and consistency with galaxy evolution expectations.