Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Few-step diffusion distillation has become increasingly mature for 4-8-step generation, yet pushing further to 2 steps remains challenging. In this work, we introduce Z-Image Turbo++, a high-quality 2-step image generation model distilled from the 8-step Z-Image Turbo teacher. Our method addresses the central bottlenecks of increased task difficulty and limited model capacity in 2-step generation ...
We are entering a new era of composite model architectures that integrate diverse components such as vision encoders, language backbones, diffusion and flow heads, audio codecs, action generators, and world-model predictors. Such architectures underpin a broad class of multimodal models, including unified multimodal models, omni models, speech-language models, vision-language-action policies, and ...
Spinal pathology is a leading cause of pain and disability worldwide. Spine MRI is central to clinical evaluation, yet its interpretation remains comp...
Extracting building polygon contours from high-resolution remote sensing images is a fundamental task for various mapping applications. However, the p...
This paper introduces EPS3D, a new end-to-end feed-forward framework for open-vocabulary 3D panoptic segmentation. Unlike existing methods relying on ...
Clinical artificial intelligence (AI) systems routinely produce predictions without principled quantification of uncertainty, limiting their trustwort...
End-to-end co-optimization of optical front-ends (e.g. metasurfaces) and neural network back-ends has been widely applied to imaging tasks, yet a form...
Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventio...
Autonomous Underwater Vehicles (AUVs) traditionally rely on complex, heavily engineered pipelines for perception, path planning, and motion control. T...
Microscopy image analysis is central to modern biology, yet many available platforms remain inaccessible to non-specialist users because they require ...
Hyperspectral imaging provides rich spectral information for quantitative remote sensing, yet hyperspectral sensors remain costly and thus unavailable...
Cell-type extraction is an important task in biomedical text mining because biomedical literature contains evidence about cell types and cell-type-rel...
Protein structure prediction via AlphaFold2 has revolutionized drug discovery, yet its end-to-end execution remains computationally intensive. While G...
Neuroimaging based pain decoding faces two underappreciated challenges: between subject variability that prevents classifiers from generalizing across...
The problem of object pose and shape estimation has seen key advancements lately. Encoder-decoder (e.g., SAM3D, LRM, CRISP) and diffusion-based models...
While the expansion of spatial omics has revolutionized our ability to dissect tissue architecture, the accumulation of incompatible computational met...
Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are rarely used as end-to-end survival models because ...
Real-world image restoration is challenging due to complex and interacting mixed degradations. Recent agent-based approaches address this problem by c...
While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reaso...
Membrane transport is a fundamental biological process with profound implications for pharmacology, biotechnology, and microbiology. While computation...