Universal precautions

CARE-Edit: Condition-Aware Routing of Experts for Contextual Image Editing

Unified diffusion editors often rely on a fixed, shared backbone for diverse tasks, suffering from task interference and poor adaptation to heterogeneous demands (e.g., local vs global, semantic vs photometric). In particular, prevalent ControlNet and OmniControl variants combine multiple conditioning signals (e.g., text, mask, reference) via static concatenation or additive adapters which cannot ...

RoboPCA: Pose-centered Affordance Learning from Human Demonstrations for Robot Manipulation

Understanding spatial affordances -- comprising the contact regions of object interaction and the corresponding contact poses -- is essential for robots to effectively manipulate objects and accomplish diverse tasks. However, existing spatial affordance prediction methods mainly focus on locating the contact regions while delegating the pose to independent pose estimation approaches, which can lea...

Match4Annotate: Propagating Sparse Video Annotations via Implicit Neural Feature Matching

Acquiring per-frame video annotations remains a primary bottleneck for deploying computer vision in specialized domains such as medical imaging, where...

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion

While recent multimodal large language models (MLLMs) have made impressive strides, they predominantly employ a conventional autoregressive architectu...

Deep Learning-based Differentiation of Drug-induced Liver Injury and Autoimmune Hepatitis: A Pathological and Computational Approach

Drug-induced liver injury (DILI) is an acute inflammatory liver disease caused not only by prescription and over-the-counter medications but also by h...

SurvHTE-Bench: A Benchmark for Heterogeneous Treatment Effect Estimation in Survival Analysis

Estimating heterogeneous treatment effects (HTEs) from right-censored survival data is critical in high-stakes applications such as precision medicine...

Mask-aware inference with State-Space Models

Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For Co...

Cultryx: Precision Diagnostic Stewardship for Blood Cultures Using Machine Learning

Background: The 2024 blood culture bottle shortage brought diagnostic resource allocation to the forefront, reflecting persistent, foundational challe...

Improved prediction of virus-human protein-protein interactions by incorporating network topology and viral molecular mimicry

The protein-protein interactions (PPIs) between viruses and human play crucial roles in viral infections. Although numerous computational approaches h...

Explainable AI for end-to-end pathogen target discovery and molecular design

Drug discovery is often constrained by target identification, a bottleneck especially acute in antimicrobial development and the fight against emergin...

Let Your Image Move with Your Motion! -- Implicit Multi-Object Multi-Motion Transfer

Motion transfer has emerged as a promising direction for controllable video generation, yet existing methods largely focus on single-object scenarios ...

GuiDINO: Rethinking Vision Foundation Model in Medical Image Segmentation

Foundation vision models are increasingly adopted in medical image analysis. Due to domain shift, these pretrained models misalign with medical image ...

FREE-Edit: Using Editing-aware Injection in Rectified Flow Models for Zero-shot Image-Driven Video Editing

Image-driven video editing aims to propagate edit contents from the modified first frame to the rest frames. The existing methods usually invert the s...

AG-VAS: Anchor-Guided Zero-Shot Visual Anomaly Segmentation with Large Multimodal Models

Large multimodal models (LMMs) exhibit strong task generalization capabilities, offering new opportunities for zero-shot visual anomaly segmentation (...

What You Read is What You Classify: Highlighting Attributions to Text and Text-Like Inputs

At present, there are no easily understood explainable artificial intelligence (AI) methods for discrete token inputs, like text. Most explainable AI ...

SPRITETOMESH: Automatic Mesh Generation for 2D Skeletal Animation Using Learned Segmentation and Contour-Aware Vertex Placement

We present SPRITETOMESH, a fully automatic pipeline for converting 2D game sprite images into triangle meshes compatible with skeletal animation frame...

Mask-HybridGNet: Graph-based segmentation with emergent anatomical correspondence from pixel-level supervision

Graph-based medical image segmentation represents anatomical structures using boundary graphs, providing fixed-topology landmarks and inherent populat...

Deep learning extracts MoA-specific signatures from high-throughput images of chemically and genetically perturbed Corynebacteria

Tuberculosis (TB) is the worldwide leading infectious killer due to a single pathogen and increasing antimicrobial resistance (AMR) makes it imperativ...

Pushing the Limits of Inverse Lithography with Generative Reinforcement Learning

Inverse lithography (ILT) is critical for modern semiconductor manufacturing but suffers from highly non-convex objectives that often trap optimizatio...

Genomic-island cassette architecture drives pathogenic Enterococcus cecorum lineages: Cassette2Vec-EC, a structural genomics and machine-learning framework

Mobile genetic elements and genomic islands (GIs) frequently encode antibiotic resistance and host-adaptation cargo, yet routine genome comparison pip...