Medicare

Improving Medicare Fraud Detection Accuracy in Deep Learning by Exploring Feature Selection and Data Sampling Techniques.

Fraud in the health landscape is an aggravating issue, with far-reaching consequences burdening the financial stability of the health industry and threatening the quality of medical care. It results from vulnerabilities within the current healthcare framework that are exploited by the fraudsters in their favor. In spite of many developed models that aim to detect fraudulent patterns in insurance c...

GNNVerifier: Graph-based Verifier for LLM Task Planning

Large language models (LLMs) facilitate the development of autonomous agents. As a core component of such agents, task planning aims to decompose complex natural language requests into concrete, solvable sub-tasks. Since LLM-generated plans are frequently prone to hallucinations and sensitive to long-context prom-pts, recent research has introduced plan verifiers to identify and correct potential ...

GNNVerifier: Graph-based Verifier for LLM Task Planning

Large language models (LLMs) facilitate the development of autonomous agents. As a core component of such agents, task planning aims to decompose comp...

Clinically Aware Synthetic Image Generation for Concept Coverage in Chest X-ray Models

The clinical deployment of AI diagnostic models demands more than benchmark accuracy - it demands robustness across the full spectrum of disease prese...

Walking Further: Semantic-aware Multimodal Gait Recognition Under Long-Range Conditions

Gait recognition is an emerging biometric technology that enables non-intrusive and hard-to-spoof human identification. However, most existing methods...

Efficient Federated Conformal Prediction with Group-Conditional Guarantee

Deploying trustworthy AI systems requires principled uncertainty quantification. Conformal prediction (CP) is a widely used framework for constructing...

Continual Few-shot Adaptation for Synthetic Fingerprint Detection

The quality and realism of synthetically generated fingerprint images have increased significantly over the past decade fueled by advancements in gene...

PET-F2I: A Comprehensive Benchmark and Parameter-Efficient Fine-Tuning of LLMs for PET/CT Report Impression Generation

PET/CT imaging is pivotal in oncology and nuclear medicine, yet summarizing complex findings into precise diagnostic impressions is labor-intensive. W...

When should we trust the annotation? Selective prediction for molecular structure retrieval from mass spectra

Machine learning methods for identifying molecular structures from tandem mass spectra (MS/MS) have advanced rapidly, yet current approaches still exh...

Perseus: Lineage-Aware Refinement of Kraken2 Taxonomic Classification for Long Read Metagenomes

Motivation: Long-read metagenomic sequencing improves assembly contiguity and enables genome-resolved analysis of complex microbial communities, but a...

How Long Can Unified Multimodal Models Generate Images Reliably? Taming Long-Horizon Interleaved Image Generation via Context Curation

Unified multimodal models hold the promise of generating extensive, interleaved narratives, weaving text and imagery into coherent long-form stories. ...

LucidNFT: LR-Anchored Multi-Reward Preference Optimization for Generative Real-World Super-Resolution

Generative real-world image super-resolution (Real-ISR) can synthesize visually convincing details from severely degraded low-resolution (LR) inputs, ...

AI End-to-End Radiation Treatment Planning Under One Second

Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning time and inter-planner variability, improving effic...

Show Your Work: Verbatim Evidence Requirements and Automated Assessment for Large Language Models in Biomedical Text Processing

Purpose: Large language models (LLMs) are used for biomedical text processing, but individual decisions are often hard to audit. We evaluated whether ...

Helios: Real Real-Time Long Video Generation Model

We introduce Helios, the first 14B video generation model that runs at 19.5 FPS on a single NVIDIA H100 GPU and supports minute-scale generation while...

Design and Rationale of the My Heart Counts Cardiovascular Health Study: a Large-Scale, Fully Digital Biobank, and Randomized Trial of Large Language Model-Driven Coaching of Physical Activity

Background: Cardiovascular disease remains the leading cause of global morbidity and mortality. The original My Heart Counts smartphone application de...

Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions

Selective conformal prediction can yield substantially tighter uncertainty sets when we can identify calibration examples that are exchangeable with t...

HeroGS: Hierarchical Guidance for Robust 3D Gaussian Splatting under Sparse Views

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach in novel view synthesis, combining photorealistic rendering with real-time e...

Act or Defer: Error-Controlled Decision Policies for Medical Foundation Models

Clinical deployment of foundation models requires decision policies that operate under explicit error budgets, such as a cap on false-positive clinica...

A Fast and Practical Column Generation Approach for Identifying Carcinogenic Multi-Hit Gene Combinations

Cancer is often driven by specific combinations of an estimated two to nine gene mutations, known as multi-hit combinations. Identifying these combina...