Prescriptions

LERD: Latent Event-Relational Dynamics for Neurodegenerative Classification

Alzheimer's disease (AD) alters brain electrophysiology and disrupts multichannel EEG dynamics, making accurate and clinically useful EEG-based diagnosis increasingly important for screening and disease monitoring. However, many existing approaches rely on black-box classifiers and do not explicitly model the underlying dynamics that generate observed signals. To address these limitations, we prop...

Deep Agentic Variant Prioritisation for Expert Level Genetic Diagnosis Fast at Scale

Abstract. Genetic diagnosis remains a formidable challenge characterized by a diagnostic odyssey that spans years, with over half of rare disease patients remaining undiagnosed affecting more than 300 million people on earth. Clinicians must navigate through thousands of candidate variants against a noisy and fragmented literature landscape, a task that overwhelms human cognitive capacity and conv...

Drug-Target Interaction Prediction with PIGLET

Drug-target interaction (DTI) prediction is a key task for computed-aided drug development that has been widely approached by deep learning models. De...

Collaborative large language models (LLMs) are all you need for screening in systematic reviews

Background: The ability of large language models (LLMs) to work collaboratively and screen studies in a systematic review (SR) is under-explored. Henc...

MolDeBERTa: Foundational Model for Physicochemical and Structural-Informed Molecular Representation Learning

Foundational models that learn the language of molecules are essential for accelerating the material and drug discovery. These self-learning models ca...

Zero-shot HOI Detection with MLLM-based Detector-agnostic Interaction Recognition

Zero-shot Human-object interaction (HOI) detection aims to locate humans and objects in images and recognize their interactions. While advances in ope...

Multimodal gene embeddings for drug-target prediction and lineage reconstruction

Understanding how gene function emerges across molecular, cellular, and pharmacologic contexts remains a central challenge in systems biology and drug...

GOT-JEPA: Generic Object Tracking with Model Adaptation and Occlusion Handling using Joint-Embedding Predictive Architecture

The human visual system tracks objects by integrating current observations with previously observed information, adapting to target and scene changes,...

Integrating Affordances and Attention models for Short-Term Object Interaction Anticipation

Short Term object-interaction Anticipation consists in detecting the location of the next active objects, the noun and verb categories of the interact...

Index Light, Reason Deep: Deferred Visual Ingestion for Visual-Dense Document Question Answering

Existing multimodal document question answering methods universally adopt a supply-side ingestion strategy: running a Vision-Language Model (VLM) on e...

Visual RAG Toolkit: Scaling Multi-Vector Visual Retrieval with Training-Free Pooling and Multi-Stage Search

Multi-vector visual retrievers (e.g., ColPali-style late interaction models) deliver strong accuracy, but scale poorly because each page yields thousa...

Are Two LLMs Better Than One? A Student-Teacher Dual-Head LLMs Architecture for Pharmaceutical Content Optimization

Large language models (LLMs) are increasingly used to create content in regulated domains such as pharmaceuticals, where outputs must be scientificall...

Data-Driven Multimodal Subtyping Reveals Differential Cognitive Risk and Treatment Effects in the All of Us Cohort

INTRODUCTION: Cognitively unimpaired (CU) adults show substantial variation in their risk of developing mild cognitive impairment (MCI), yet most subt...

Multimodal Priors-Augmented Text-Driven 3D Human-Object Interaction Generation

We address the challenging task of text-driven 3D human-object interaction (HOI) motion generation. Existing methods primarily rely on a direct text-t...

Identifying Evidence-Based Nudges in Biomedical Literature with Large Language Models

We present a scalable, AI-powered system that identifies and extracts evidence-based behavioral nudges from unstructured biomedical literature. Nudges...

Fully Differentiable Bidirectional Dual-Task Synergistic Learning for Semi-Supervised 3D Medical Image Segmentation

Semi-supervised learning relaxes the need of large pixel-wise labeled datasets for image segmentation by leveraging unlabeled data. The scarcity of hi...

Hand2World: Autoregressive Egocentric Interaction Generation via Free-Space Hand Gestures

Egocentric interactive world models are essential for augmented reality and embodied AI, where visual generation must respond to user input with low l...

VideoAfford: Grounding 3D Affordance from Human-Object-Interaction Videos via Multimodal Large Language Model

3D affordance grounding aims to highlight the actionable regions on 3D objects, which is crucial for robotic manipulation. Previous research primarily...

GEBench: Benchmarking Image Generation Models as GUI Environments

Recent advancements in image generation models have enabled the prediction of future Graphical User Interface (GUI) states based on user instructions....

VLM-Guided Iterative Refinement for Surgical Image Segmentation with Foundation Models

Surgical image segmentation is essential for robot-assisted surgery and intraoperative guidance. However, existing methods are constrained to predefin...