large language models

Toward Secure Code Generation: Bridging Correctness and Security via Task-Adaptive Vulnerability Modeling and Execution-Based Benchmarking

Experiments across multiple LLM backbones show that SecAwareCoder consistently improves Pass@1 and security robustness over prompting and analyzer-driven baselines, narrowing the security--correctness gap in LLM code generation.

Continual Learning for Sequential Personalization of Small Language Models: A Stability Monitoring Analysis

It is shown that lightweight reference set distributional diagnostics can reveal model-specific instability patterns during sequential LoRA personalization of SLMs, including cases where task-level metrics alone hide harmful adaptation.

Exploring the Potential of Diffusion Large Language Models in Code Generation

This study presents the first empirical study of diffusion LLMs for code generation and explores factors impacting the effectiveness and efficiency of diffusion LLMs, and provides practical guidance.

ACCELERATING PATHOLOGY REPORT DIGITIZATION: A MULTI-ENGINE OCR AND LLM FRAMEWORK FOR HEALTHCARE APPLICATIONS

Digitization and structuring of pathology reports are essential in modern healthcare for enhancing patient care, data analytics, and medical research. This study presents a framework called Dual-integrated Text Extraction using Hybrid OCR Engines (DiText-OCR), which leverages multiple OCR tools and domain-specific dict...

ACCELERATING PATHOLOGY REPORT DIGITIZATION: A MULTI-ENGINE OCR AND LLM FRAMEWORK FOR HEALTHCARE APPLICATIONS

Digitization and structuring of pathology reports are essential in modern healthcare for enhancing patient care, data analytics, and medical research. This study presents a framework called Dual-integrated Text Extraction using Hybrid OCR Engines (DiText-OCR), which leverages multiple OCR tools and domain-specific dict...

Universal Intelligent Document Management System Using OCR, Retrieval-Augmented Generation, and Large Language Models

Abstract The rapid growth of digital information has significantly increased the need for intelligent systems capable of managing, understanding, and retrieving knowledge from diverse document formats. Traditional document management systems primarily focus on storage and indexing, requiring users to manually search fo...

Universal Intelligent Document Management System Using OCR, Retrieval-Augmented Generation, and Large Language Models

Abstract The rapid growth of digital information has significantly increased the need for intelligent systems capable of managing, understanding, and retrieving knowledge from diverse document formats. Traditional document management systems primarily focus on storage and indexing, requiring users to manually search fo...

An Explainable Multimodal Deep Learning Framework for Alzheimer's Disease Classification Using MRI, PET, and Clinical Data

Abstract Alzheimer's disease (AD) often remains undetected until memory loss and cognitive decline become clinically apparent, at which point substantial neurological damage has already occurred. Early and reliable diagnosis therefore, remains one of the most pressing challenges in dementia care. This study presents a...

An Explainable Multimodal Deep Learning Framework for Alzheimer's Disease Classification Using MRI, PET, and Clinical Data

Abstract Alzheimer's disease (AD) often remains undetected until memory loss and cognitive decline become clinically apparent, at which point substantial neurological damage has already occurred. Early and reliable diagnosis therefore, remains one of the most pressing challenges in dementia care. This study presents a...

Exploring 3D point clouds with multimodal large language model (MLLM): A review

Knowledge graph-enhanced large language models for decision support in coastal waterway aids to navigation

Multi-grained image-text retrieval in farmland remote sensing via multimodal large language models