Identifying and Reporting Dependent Adult abuse

Consistency Beyond Contrast: Enhancing Open-Vocabulary Object Detection Robustness via Contextual Consistency Learning

Recent advances in open-vocabulary object detection focus primarily on two aspects: scaling up datasets and leveraging contrastive learning to align language and vision modalities. However, these approaches often neglect internal consistency within a single modality, particularly when background or environmental changes occur. This lack of consistency leads to a performance drop because the model ...

HINT: Composed Image Retrieval with Dual-path Compositional Contextualized Network

Composed Image Retrieval (CIR) is a challenging image retrieval paradigm. It aims to retrieve target images from large-scale image databases that are consistent with the modification semantics, based on a multimodal query composed of a reference image and modification text. Although existing methods have made significant progress in cross-modal alignment and feature fusion, a key flaw remains: the...

Agentic Automation of BT-RADS Scoring: End-to-End Multi-Agent System for Standardized Brain Tumor Follow-up Assessment

The Brain Tumor Reporting and Data System (BT-RADS) standardizes post-treatment MRI response assessment in patients with diffuse gliomas but requires ...

Anatomical Prior-Driven Framework for Autonomous Robotic Cardiac Ultrasound Standard View Acquisition

Cardiac ultrasound diagnosis is critical for cardiovascular disease assessment, but acquiring standard views remains highly operator-dependent. Existi...

CFCML: A Coarse-to-Fine Crossmodal Learning Framework For Disease Diagnosis Using Multimodal Images and Tabular Data

In clinical practice, crossmodal information including medical images and tabular data is essential for disease diagnosis. There exists a significant ...

VisBrowse-Bench: Benchmarking Visual-Native Search for Multimodal Browsing Agents

The rapid advancement of Multimodal Large Language Models (MLLMs) has enabled browsing agents to acquire and reason over multimodal information in the...

TrialScout links published results to trial registrations using a large language model

Background: Multiple stakeholders need to locate results of registered clinical trials but frequently struggle to find them. Summary results of clinic...

Collaborative Temporal Feature Generation via Critic-Free Reinforcement Learning for Cross-User Sensor-Based Activity Recognition

Human Activity Recognition using wearable inertial sensors is foundational to healthcare monitoring, fitness analytics, and context-aware computing, y...

VisBrowse-Bench: Benchmarking Visual-Native Search for Multimodal Browsing Agents

The rapid advancement of Multimodal Large Language Models (MLLMs) has enabled browsing agents to acquire and reason over multimodal information in the...

Prototype-Based Knowledge Guidance for Fine-Grained Structured Radiology Reporting

Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must make man...

Ensuring Safety in Automated Mechanical Ventilation through Offline Reinforcement Learning and Digital Twin Verification

Mechanical ventilation (MV) is a life-saving intervention for patients with acute respiratory failure (ARF) in the ICU. However, inappropriate ventila...

Bridging the Skill Gap in Clinical CBCT Interpretation with CBCTRepD

Generative AI has advanced rapidly in medical report generation; however, its application to oral and maxillofacial CBCT reporting remains limited, la...

Streaming Autoregressive Video Generation via Diagonal Distillation

Large pretrained diffusion models have significantly enhanced the quality of generated videos, and yet their use in real-time streaming remains limite...

Streaming Autoregressive Video Generation via Diagonal Distillation

Large pretrained diffusion models have significantly enhanced the quality of generated videos, and yet their use in real-time streaming remains limite...

Predictors of COVID-19 hospital outcomes: a machine learning analysis of the National COVID Cohort Collaborative

Predicting hospital outcomes for patients with severe acute respiratory infections is critical for risk stratification and resource planning, yet hete...

PureCC: Pure Learning for Text-to-Image Concept Customization

Existing concept customization methods have achieved remarkable outcomes in high-fidelity and multi-concept customization. However, they often neglect...

Functional Locality-Aligned Learning Reveals Structure-Function Causality in Enzyme Kinetics

Accurate estimation of enzyme kinetic parameters is essential for enzyme engineering and industrial biocatalysis, yet their experimental measurement r...

Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset

Infrared image super-resolution (IISR) under real-world conditions is a practically significant yet rarely addressed task. Pioneering works are often ...

RVN-Bench: A Benchmark for Reactive Visual Navigation

Safe visual navigation is critical for indoor mobile robots operating in cluttered environments. Existing benchmarks, however, often neglect collision...

Footprint-Guided Exemplar-Free Continual Histopathology Report Generation

Rapid progress in vision-language modeling has enabled pathology report generation from gigapixel whole-slide images, but most approaches assume stati...