HypEHR is a hyperbolic embedding model for EHR data that uses Lorentzian geometry and hierarchy-aware pretraining to answer clinical questions nearly as well as large language models but with much smaller size.
arXiv preprint arXiv:2303.06628 , year=
3 Pith papers cite this work. Polarity classification is still indexing.
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ZooClaw-FashionSigLIP2 applies distilled full fine-tuning plus WiseFT interpolation to SigLIP2-base and reports outperforming LoRA, larger backbones, and external data on fashion retrieval benchmarks while releasing a new benchmark and bias analysis.
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HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering
HypEHR is a hyperbolic embedding model for EHR data that uses Lorentzian geometry and hierarchy-aware pretraining to answer clinical questions nearly as well as large language models but with much smaller size.
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ZooClaw-FashionSigLIP2: Distilled Fine-tuning for Robust Fashion Retrieval
ZooClaw-FashionSigLIP2 applies distilled full fine-tuning plus WiseFT interpolation to SigLIP2-base and reports outperforming LoRA, larger backbones, and external data on fashion retrieval benchmarks while releasing a new benchmark and bias analysis.
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