large language models

Social Robotics and Human–Robot Communication

This chapter explores the ergonomic, cognitive, and psychological mechanisms underpinning human–robot communication, focusing on the role of social robots in shaping human perception, behaviour, and socio-emotional engagement. By analysing factors such as robot design, embodiment, and communication modalities, the chap...

RAG vs. GraphRAG for Industrial Technical Documentation: A Controlled Evaluation on Laser Manufacturing Manuals

Retrieval-Augmented Generation (RAG) enables large language models to answer questions grounded in external documents, yet its effectiveness on specialized industrial documentation remains underexplored. We present, to our knowledge, the first controlled comparison of conventional vector-based RAG and graph-augmented R...

From Classification to Cross-Modal Understanding: Leveraging Vision- Language Models for Fine-Grained Renal Pathology

Fine-grained glomerular subtyping is essential for kidney biopsy interpretation, yet it presents a harder setting than the broad organ- or disease-level recognition tasks commonly used in vision-language model (VLM) evaluation. In this task, all categories arise within the same renal microanatomic unit, and clinically...

Multimodal Large Language Models for Psychosocial Risk Management in Construction

This repository contains the datasets, supplementary workbooks, visualization code, and supporting materials used in the study. The materials are provided to support transparency, reproducibility, and audit purposes.

Receipts Over Genius: An Audited Account of an 18-Month, AI-Assisted, Solo Invention Cycle

SQUIRL OS RESEARCH DISCLOSURE - READ FIRST: This work is part of an open-book, AI-assisted research program produced under bifurcated governance (a probabilistic AI agent drafts; a deterministic human key approves; a boundary-layer audit checks claims against receipt archives). Audit-and-correction is doctrine: superse...

Collaborative Multi-Agent LLM Frameworks for Automated Legacy Software Modernization

Legacy software modernization is a critical challenge for organizations seeking to improve system maintainability, scalability, security, and compatibility with contemporary technologies while preserving existing business logic. Traditional modernization approaches often require substantial manual effort, extensive dom...

General-purpose LLMs as constrained crystal composition generators

Abstract The targeted discovery of inorganic materials remains challenging due to the vastness of compositional design spaces and the high cost of exhaustive screening. Task-specific generative artificial intelligence represents a particularly efficient alternative to screening, yet demands tedious collection of traini...

LLMCloc: Compiler bug localization via large language model-based root cause analysis

VulnTACT: Predicting ATT&CK for ICS Tactics and Techniques from Vulnerability Information Using Domain-Adapted Large Language Models

A large language model and knowledge graph collaborative generative framework for aircraft manufacturing system design in MBSE

Performance of Large Language Models in Answering Juvenile Systemic Lupus Erythematosus Questions: A Blinded Expert-based Comparative Study.

BACKGROUND Large language models are increasingly used to obtain medical information, but their performance in juvenile systemic lupus erythematosus remains insufficiently characterized. OBJECTIVE To compare expert-rated response quality and clinical relevance across 4 artificial intelligence (AI) models using standa...

Shallow Lexical, Deep Source: A Hierarchical Examination of LLM Bias in News Evaluation

Large language models (LLMs) increasingly mediate how people read the news, but how deeply their evaluations are shaped by textual cues remains unclear. This study manipulated news coverage of the Columbia Gaza campus protests at two levels: a shallow, lexical level (adjective framing: left, right, neutral, original) a...