Large-scale HPC evaluation of Qdrant, Milvus, and Weaviate reveals that workload patterns limit scaling and extra cores can reduce throughput, exposing a cloud-to-HPC design mismatch.
arXiv preprint arXiv:2312.07814 , year=
5 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
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ASTRA unifies heterogeneous pathology foundation-model representations for pan-cancer classification and weakly supervised tumor localization using only slide-level structured annotations.
Med-Gemini sets new records on 10 of 14 medical benchmarks including 91.1% on MedQA-USMLE, beats GPT-4V by 44.5% on multimodal tasks, and surpasses humans on medical text summarization.
CapCLIP uses pathology-aware text captions to align WCE images in a vision-language space, outperforming standard models in zero-shot classification and retrieval on unseen data.
The paper surveys data-centric strategies for foundation models in computational healthcare and supplies a curated list of related models and datasets.
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When More Cores Hurts: The Vector Database Scaling Paradox in HPC
Large-scale HPC evaluation of Qdrant, Milvus, and Weaviate reveals that workload patterns limit scaling and extra cores can reduce throughput, exposing a cloud-to-HPC design mismatch.
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Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localization
ASTRA unifies heterogeneous pathology foundation-model representations for pan-cancer classification and weakly supervised tumor localization using only slide-level structured annotations.
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Capabilities of Gemini Models in Medicine
Med-Gemini sets new records on 10 of 14 medical benchmarks including 91.1% on MedQA-USMLE, beats GPT-4V by 44.5% on multimodal tasks, and surpasses humans on medical text summarization.
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CapCLIP: A Vision-Language Representation Alignment Approach for Wireless Capsule Endoscopy Analysis
CapCLIP uses pathology-aware text captions to align WCE images in a vision-language space, outperforming standard models in zero-shot classification and retrieval on unseen data.
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Data-Centric Foundation Models in Computational Healthcare: A Survey
The paper surveys data-centric strategies for foundation models in computational healthcare and supplies a curated list of related models and datasets.