Prescriptions

Confidence Scores in Open-Vocabulary Detection Are a Biased Mixture of Scale and Semantics

Foundation models such as CLIP have enabled open-vocabulary object detectors that generalise to novel categories via vision-language similarity. However, the confidence scores these detectors produce are not reliable localization probability estimates: they conflate visual scale and semantic query specificity with the true detection signal. Through controlled experiments on COCO across three found...

DiffEEG: A Self-Supervised Denoising Diffusion Model for Learning EEG Generic Representations

Deep learning for EEG-based seizure detection faces critical challenges: severe annotation scarcity and extreme class imbalance, where ictal events comprise less than 10\% of clinical recordings. We present DiffEEG, a 9.6M-parameter self-supervised foundation model that addresses both limitations through denoising diffusion pre-training and reinforcement learning (RL)-based fine-tuning. Pre-traine...

GFR-SAM: Training-Free Referring Camouflaged Object Segmentation via Cross-Image Prompting

Referring Camouflaged Object Detection (Ref-COD) requires segmenting hidden targets guided by reference cues. While supervised methods are annotation-...

Deceptive Grounding: Entity Attribution Failure in Clinical Retrieval-Augmented Generation

Retrieval-augmented generation evaluation checks whether model claims are factually grounded in retrieved documents. It does not check whether retriev...

Interaction-finder: automated literature-based discovery of biological entity associations with quote-level provenance

Identifying interactions between biological entities is a cornerstone of molecular research, but assembling such lists from the literature is slow and...

Data-driven Prediction of Fifteen-Year All-Cause Mortality among 2.3 Million Individuals in the VA

We present a data-driven framework to predict 15-year all-cause mortality using outpatient administrative records for 2.3 million Veterans in the larg...

Biological Network Organization, Not Generic Graph Topology, Drives Graph-Based Gene Essentiality Prediction

Predicting gene essentiality across cellular contexts is a central challenge in computational biology, with implications for identifying cancer vulner...

Effect of initiating an ARB- versus ACEI-based regimen on dementia risk, a target trial emulation of 2.5 million US Veterans

Background: Hypertension is a modifiable risk factor for dementia, yet the comparative effectiveness of angiotensin receptor blockers (ARBs) versus an...

A large language model-assisted workflow for generating a living evidence base for climate-sensitive foodborne disease

Abstract Climate change is altering environmental conditions that influence foodborne disease transmission, yet traditional systematic reviews cannot ...

Generative Drug Design in a Loop with dtSFM

Directed evolution consisting of iterative rounds of diversification, selection, and counter-selection, underlies modern protein and antibody engineer...

Screening Lipid Nanoparticles through Structure-Ratio Alignment

Lipid Nanoparticles (LNPs) are widely used as delivery systems for nucleic acid therapeutics, where transfection efficiency is determined by both the ...

Complexity-Budgeted, Interaction-Aware Interpretable Model for Tabular Data

Inherently interpretable classifiers for tabular data typically rely on sparse features, rules, or patterns that users can inspect directly. The margi...

Asymmetric Focal Loss Improves Graph Neural Network Prediction of Drug-Drug Interactions

Background: Graph neural networks improve computational prediction of polypharmacy side effects, but standard binary cross-entropy training allocates ...

A Quiet Failure in Calibrated Virtual Screening: Marginal Conformal Prediction Under-Covers the Minority Class, and a Class-Conditional Fix Recovers It

Conformal prediction is being adopted in drug discovery to put an honest number on model reliability: pick an error rate alpha, and the method returns...

Deep-Interact Studio: An Interactive Deep Learning Model Building Platform for Biomolecular Interaction Prediction

Motivation: Deep learning has rapidly become essential for predicting biomolecular interactions; however, most web-tools expose only a single, pre-bui...

Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding

Multi-Pool Chemical Exchange Saturation Transfer (CEST) MRI provides valuable metabolic information but is clinically limited by long acquisition time...

UI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation

Large language models (LLMs) have demonstrated growing competence in web page generation. However, existing text-driven approaches rely on complex pro...

The Large Cancer Assistant (LCA): A Model-Agnostic Orchestration Framework for Scalable Clinical Decision Support in Oncology

- Objective: Multimodal deep learning models in oncology are currently limited by monolithic designs that rigidly couple data ingestion, clinical rout...

REVIVE: A Multi-Modal Framework for Vandalism Detection and Recovery in Autonomous Vehicles

Autonomous vehicles (AVs) face increasing threats from vandalism-induced occlusion attacks (VOAs) that compromise camera-based perception. While detec...

Predicting Therapeutic Outcome via Aligning Patient-Specific Knowledge Graph and Gene-Level Perturbation Representations

Accurate prediction of patient-specific therapeutic response from pre-treatment transcriptomes is hindered by the scarcity of matched clinical respons...