Public Health & Policy

Work Force

Latest AI and machine learning research in work force for healthcare professionals.

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Stage-Aware Adaptation and Distribution Calibration for Subject-Driven Personalized Text-to-Image Generation

Subject-driven personalized text-to-image generation requires a pretrained diffusion model to acquir...

SPEAR: A Simulator for Photorealistic Embodied AI Research

Interactive simulators have become powerful tools for training embodied agents and generating synthe...

InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics

Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms a...

EMPURPLE: A Free Lunch for Diffusion Distillation based on the Information Bottleneck

Diffusion models achieve impressive image-generation quality but remain expensive at inference time....

Embracing Intra-Class Heterogeneity for Semi-Supervised Medical Image Segmentation: From Diversity to Precision

Due to the scarcity of expert-annotated data, Semi-Supervised Medical Image Segmentation (SSMIS) has...

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches

Single image super-resolution aims to reconstruct high-resolution (HR) images from low-resolution (L...

Visual Semantic Entropy: Do Vision Language Models Recognize Visual Ambiguity?

Vision-language models can produce confident answers on visually ambiguous inputs, resulting in bias...

Retention, not flux: endpoint confounding caps computational prediction of peptide skin penetration, with a delivery-aware reframing

Bioactive peptides are now central to cosmetic and dermatological actives, yet predicting whether a ...

EvoSeq-ML: Advancing Data-Centric Machine Learning with Evolutionary-Informed Protein Sequence Representation and Generation

From protein structure prediction to novel protein generation, challenging protein engineering tasks...

A Natural Experiment Reveals Clinically Essential and Compliance-Driven Nursing Documentation

Despite contributing substantially to clinician burnout, nursing documentation lacks empirical evide...

Don't Settle at the Mode! Mitigating Diversity Collapse in Pretrained Flow Models via Feature Self-Guidance

State-of-the-art flow models generate stunning images from text or image prompts. However, they suff...

DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation

Subject-driven image generation faces an "Identity-Diversity Paradox", where strong identity preserv...

PsyBridge: A Hybrid Intelligent Framework for Multi-Dimensional Mental Health Assessment and Decision Support

Mental health assessment commonly relies on isolated screening instruments or data-driven models tha...

Semantic Browsing: Controllable Diversity for Image Generation

Modern text-to-image models excel in visual fidelity and prompt adherence. However, this strict adhe...

Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs

Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational ...

Data-Forcing Distillation: Restoring Diversity and Fidelity in Few-Step Video Generation

Recent progress has shown promise in distilling multi-step video diffusion models into efficient few...

GermRL: Alleviating The Germline Bias In Autoregressive Antibody Language Models Through Reinforcement Learning

Antibodies are powerful therapeutics whose antigen specificity arises from sequence diversity shaped...

An AI-Powered Trisomy 21 Research Assistant

Down syndrome, caused by trisomy 21, increases the risk of diverse co-occurring conditions. With mor...

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