ADHD/ADD

Beyond Injection Detection: A Positive-Security Prompt Firewall that Closes the Scope and PHI Gap SOTA Classifiers Miss in Healthcare

Large language models embedded in autonomous agents process trusted instructions and untrusted data in one context window, leaving them open to direct and indirect prompt injection. In healthcare this is not hypothetical: a 2025 JAMA Network Open study found commercial medical LLMs followed injected instructions in 94.4% of simulated patient encounters, including life threatening recommendations ....

Accelerating Reproducible Research in Synthetic EHR Generation

The generation of high-fidelity synthetic Electronic Health Records (EHR) is crucial for advancing medical research while preserving patient privacy. However, head-to-head comparison of existing generative models is hindered by disjointed codebases, incompatible data loaders, conflicting library dependencies, and inconsistent evaluation protocols. To address these gaps, we introduce a lightweight,...

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising. We argue th...

LoomVideo: Unifying Multimodal Inputs into Video Generation and Editing

Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs is a promising yet challenging frontier f...

Multiple versus pairwise sequence alignments for protein phylogenetics using foundation models

Phylogenetic inference is a common task in molecular and evolutionary biology and has conventionally required a multiple sequence alignment (MSA), a s...

Identification of Heterogeneous Cortical Thickness Patterns Associated with Prenatal Gestational Diabetes Exposure: A SuStaIn-Based Subtyping Study

Importance: Prenatal exposure to gestational diabetes mellitus (GDM) has been associated with adverse metabolic, neurodevelopmental, and psychiatric o...

Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models

Concept unlearning aims to erase a target concept from a pretrained text-to-image diffusion model without retraining. Closed-form methods are attracti...

First, do no harm: Breaking suicidogenic echo chambers in media recommendation

Recommender systems generally optimises user engagement, but this approach is dangerous in mental health contexts. When vulnerable users show signs of...

Retrospective cohort study extracting coexisting background breast-lesion features from stage I-III invasive breast cancer

Background Background breast features are frequently noted in pathology reports alongside invasive breast cancer but rarely factor into prognosis or t...

NeRF-based Spacecraft Reconstruction from Close-Range Monocular Imagery Under Illumination Variability and Pose Uncertainty

Autonomous rendezvous and proximity operations around uncooperative, unknown spacecraft are critical for active debris removal and on-orbit servicing ...

Evaluating open LLMs for agentic analysis orchestration in a typical biomedical lab

Agentic tools - software environments where a large language model plans, calls external tools, executes code, and iterates with minimal human interve...

LiWi: Layering in the Wild

Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domai...

From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction

By processing electronic health records (EHRs) as natural language sequences, large language models (LLMs) have shown potential in clinical prediction...

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs

Biomedical knowledge graphs underwrite drug repurposing and clinical decision support, yet the upstream ontologies they depend on update on independen...

Simpler is not always better: Phylodynamic misspecification and deep-learning corrections

Phylodynamics bridges the gap between epidemiology and pathogen genetic data by estimating epidemiological parameters from time-scaled pathogen phylog...

Learning Discrete Autoregressive Priors with Wasserstein Gradient Flow

Discrete image tokenizers are commonly trained in two stages: first for reconstruction, and then with a prior model fitted to the frozen token sequenc...

Do Larger Models Really Win in Drug Discovery?A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

The rapid growth of molecular foundation models and general-purpose large language models has encouraged a scale-centric view of artificial intelligen...

Predicting first-onset depression in adolescents: Do general population models generalize to youth with ADHD?

Background: Most studies seeking to identify youth at increased risk for depression have developed prediction models using a limited set of risk facto...

From Prediction to Practice: A Task-Aware Evaluation Framework for Blood Glucose Forecasting

Clinical time-series forecasting is increasingly studied for decision support, yet standard aggregate metrics can obscure whether a model is actually ...

An Interpretable Deep Learning Framework Reveals Frontoparietal Control Network Hyperactivation Underlying Autism Diagnosis and Symptom Severity

BACKGROUND: Autism spectrum disorder (ASD) is marked by profound neurobiological heterogeneity, which drives inconsistent neuroimaging findings and im...