Prescriptions

Optimizing Curve-Based Selection with On-Body Surfaces in Virtual Environments

Virtual Reality (VR) interfaces often rely on linear ray-casting for object selection but struggle with precision in dense or occluded environments. This late-breaking work introduces an optimized dual-layered selection mechanism combining dynamic Bezier Curves, controlled via finger gestures, with on-body interaction surfaces to enhance precision and immersion. Bezier Curves offer fine-grained ...

Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader.

Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI) computer-aided detection (CAD) and two radiologists. The results raised concerns about the tendency of radiologists to agree with AI CAD too much (when AI CAD made an erroneous flagging) or too little (when AI CAD made a correct flagging). Purpose T...

ProAI: Proactive Multi-Agent Conversational AI with Structured Knowledge Base for Psychiatric Diagnosis

Most LLM-driven conversational AI systems operate reactively, responding to user prompts without guiding the interaction. Most LLM-driven conversati...

Unleashing the Potential of Two-Tower Models: Diffusion-Based Cross-Interaction for Large-Scale Matching

Two-tower models are widely adopted in the industrial-scale matching stage across a broad range of application domains, such as content recommendati...

KEDRec-LM: A Knowledge-distilled Explainable Drug Recommendation Large Language Model

Drug discovery is a critical task in biomedical natural language processing (NLP), yet explainable drug discovery remains underexplored. Meanwhile, ...

Learning to Generalize without Bias for Open-Vocabulary Action Recognition

Leveraging the effective visual-text alignment and static generalizability from CLIP, recent video learners adopt CLIP initialization with further r...

Scalability of the second-order reliability method for stochastic differential equations with multiplicative noise

We show how to efficiently compute asymptotically sharp estimates of extreme event probabilities in stochastic differential equations (SDEs) with sm...

One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion

Advanced image fusion methods mostly prioritise high-level missions, where task interaction struggles with semantic gaps, requiring complex bridging...

InPK: Infusing Prior Knowledge into Prompt for Vision-Language Models

Prompt tuning has become a popular strategy for adapting Vision-Language Models (VLMs) to zero/few-shot visual recognition tasks. Some prompting tec...

Improved YOLOv12 with LLM-Generated Synthetic Data for Enhanced Apple Detection and Benchmarking Against YOLOv11 and YOLOv10

This study evaluated the performance of the YOLOv12 object detection model, and compared against the performances YOLOv11 and YOLOv10 for apple dete...

Revealing Treatment Non-Adherence Bias in Clinical Machine Learning Using Large Language Models

Machine learning systems trained on electronic health records (EHRs) increasingly guide treatment decisions, but their reliability depends on the cr...

DBox: Scaffolding Algorithmic Programming Learning through Learner-LLM Co-Decomposition

Decomposition is a fundamental skill in algorithmic programming, requiring learners to break down complex problems into smaller, manageable parts. H...

Effect of Gender Fair Job Description on Generative AI Images

STEM fields are traditionally male-dominated, with gender biases shaping perceptions of job accessibility. This study analyzed gender representation...

MuCoS: Efficient Drug-Target Prediction through Multi-Context-Aware Sampling

Drug-target interactions are critical for understanding biological processes and advancing drug discovery. However, traditional methods such as Comp...

Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Review

Drug discovery remains a slow and expensive process that involves many steps, from detecting the target structure to obtaining approval from the Foo...

Beyond the Surface: Uncovering Implicit Locations with LLMs for Personalized Local News

News recommendation systems personalize homepage content to boost engagement, but factors like content type, editorial stance, and geographic focus ...

Physical Depth-aware Early Accident Anticipation: A Multi-dimensional Visual Feature Fusion Framework

Early accident anticipation from dashcam videos is a highly desirable yet challenging task for improving the safety of intelligent vehicles. Existin...

Smaller But Better: Unifying Layout Generation with Smaller Large Language Models

We propose LGGPT, an LLM-based model tailored for unified layout generation. First, we propose Arbitrary Layout Instruction (ALI) and Universal Layo...

LIDDIA: Language-based Intelligent Drug Discovery Agent

Drug discovery is a long, expensive, and complex process, relying heavily on human medicinal chemists, who can spend years searching the vast space ...

VLAS: Vision-Language-Action Model With Speech Instructions For Customized Robot Manipulation

Vision-language-action models (VLAs) have become increasingly popular in robot manipulation for their end-to-end design and remarkable performance. ...