large language models

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

Dual-stream representation learning with large language models for electricity demand forecasting

Designing Growth Mindset-Inspired Feedback Messages Tailored to Learning Behaviors Using LLM and Persuasive Strategies

This work introduces a four-part feedback message structure inspired by the growth mindset principle, which encourages students to reflect, persist, and embrace challenges, and provides an initial foundation for explainable, rule-based feedback generation that can be extended through experimentation with learners.

CrossServe: Cross-Layer Scheduling for SLO Optimization in Multi-Tenant LLM Serving

The deployment of Large Language Models (LLMs) as multi-tenant cloud services is now widespread, but maintaining high Service Level Objective (SLO) attainment across diverse tenants remains challenging. Current serving systems focus on a single layer of the stack, either using iteration-level batching or coarse-grained...

Harmonic Intelligence: Recursive Analytic Meta-Geometry, Residual-Bearing Learning, and the Geometry of Solution Types — Integrated Edition

[wAI ~ wErrors] «All models are wrong, but some are useful.» — George E. P. Box (1976) This preprint synthesizes a large exploratory notebook on metric atlases, spectral and harmonic representations, residual-bearing learning, recursive joint/meta-diagonalization, Galois and monodromy fingerprints, sheaf/cohomological...

Online Scheduling of Battery-Aware Speculative Decoding for Energy-Efficient Cloud-Edge Collaborative LLM Inference

This work designs a learning-centric algorithmic framework which employs bandit learning to address the intractability and manage draft length selection in the first subproblem and applies online learning to address the online uncertainty and manage battery states and grid-energy use in the second subproblem, both with...