Ophthalmology

When Are Reasoning-Based Guardrails Not Efficient? ResponseGuard: A Fast Vision-Language Guard for Real-Time Moderation

A vision-language AI assistant returns its answer as a stream of generated tokens. Therefore, a safety guard that watches that answer has to keep up with the stream and stop a harmful reply before a user reads it. Recent vision-language guardrails instead generate a chain of thought before they issue a verdict. They believe that step-by-step reasoning yields a safer guard. This design makes the gu...

Ocular Verification for Virtual Reality

Virtual reality (VR) headsets (e.g., Meta Quest, Apple Vision Pro) provide a seamless user experience due to their fast, frictionless interaction with the physical world in a simulated environment. User authentication relies on biometric cues such as iris in such headsets. However, traditional iris recognition protocols may not be adequate in cases of unconstrained acquisition, which is typical of...

Trace: A Taxonomy-Guided Environment for Multidomain Visual Reasoning

Reinforcement learning with verifiable rewards (RLVR) has substantially improved language-model reasoning, yet its extension to vision-language models...

LAVIFT: Latent-Action-Guided Vision Fine-Tuning for Surgical Interaction Recognition

Understanding instrument-tissue interactions is essential for context-aware surgical AI and autonomous robotic surgery. Pretrained vision-language mod...

ENTRAP-VL: A Taxonomic Probe for Dual Contextual Entrainment in Vision-Language Models

Contextual entrainment is the tendency of a model to let auxiliary context in its input pull its output, independently of whether that context is rele...

How Does Urban Context Relate to Residential Building Health? A Vision-POI Fusion Framework for Building-Level Housing Inspection

Housing-level urban physical examination is essential for identifying residential building problems and supporting targeted urban renewal. Existing au...

MissingBench-Verified: Probing Vision-Language Models' Inability to Detect Missing Object Parts

Vision Language Models (VLMs) are well known for hallucinating non-existent objects in images. Objects with missing parts present a unique challenge f...

Deep learning design and in vivo validation of Müller glia-specific cis-regulatory elements

Effective recombinant adeno-associated virus gene therapies require promoters that are compact and cell-type-specific. Ideally, promoters should also ...

Vision Normalizing Flows for the probability-informed detection of banana diseases from in-field images

Banana diseases impose severe production losses in tropical smallholder farming systems, yet accurate in-field visual diagnosis remains difficult: sym...

Norm or Direction? Decoding Vision Mambas for High-Resolution Vision

Vision Mamba models replace quadratic self-attention with linear complexity selective state space models (SSMs), emerging as efficient visual backbone...

MissingBench-Verified: Probing Vision-Language Models' Inability to Detect Missing Object Parts

Vision Language Models (VLMs) are well known for hallucinating non-existent objects in images. Objects with missing parts present a unique challenge f...

SkyEV: RGB-Event UAV detection and tracking dataset and baseline

Detecting UAVs in air spaces has become increasingly important due to UAVs widespread availability and easy usage. However, due to their small size, t...

Bounding Boxes to Improve Small Language Model Performance on Vision-Based Grading Tasks

The deployment of Small Language Models (SLMs) in educational settings offers significant advantages in terms of privacy, cost, and scalability. Howev...

OPD-IAD: From Language Judgment to Industrial Anomaly Detection via On-Policy Self-Distillation

Large vision-language models (LVLMs) have recently shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judg...

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model

While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vul...

Gaze-DETR: Top-Down Guidance Through Priority Maps for Infrared Weak-Small UAV Detection with DETR

Infrared small target detection (ISTD) remains challenging because tiny, low-contrast targets are easily overwhelmed by clutter, noise, or occlusion. ...

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models

Vision-language models (VLMs) provide a unified representation space for textual and visual information, yet their potential as general-purpose backbo...

InstructMixup: Instruction-Guided Salient Patch Editing for Robust Data Augmentation

In image and video technologies, data augmentation is widely used to improve the generalization of deep visual models, and mixup-based strategies that...

ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesis

Recent advances in multimodal generative models have enabled instruction-based image generation to move beyond semantic manipulation to knowledge-driv...

MedZone Embedder: a framework for representation learning of Japanese secondary medical care areas from a national ICU registry, characterizing intensive care provision structure and regional vulnerability

Background: In Japan, acute inpatient care is divided into approximately 335 secondary medical care areas, which serve as the basic units for planning...