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From Entropy to Calibrated Uncertainty: Training Language Models to Reason About Uncertainty
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Non-Contrastive Vision-Language Learning with Predictive Embedding Alignment
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PACMON: Pathway-guided Multi-Omics data integration for interpreting large-scale perturbation screens
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An autonomous agent for auditing and improving the reliability of clinical AI models
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Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
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Cross-Species Morphology Learning Enables Nucleic Acid-Independent Detection of Live Mutant Blood Cells
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DATS: Distance-Aware Temperature Scaling for Calibrated Class-Incremental Learning
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Differentiation hierarchy in adult B cell acute lymphoblastic leukemia at clonal resolution
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Machine Learning based Analysis for Radiomics Features Robustness in Real-World Deployment Scenarios
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MOFA-FLEX: A Factor Model Framework for Integrating Omics Data with Prior Knowledge
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