large language models

Social-Democratic and Liberal Features of the Swedish Socio-Economic Development Model (English translation of a 2012 Russian-language term paper)

English translation of a term paper (Kursovaya rabota) originally written in Russian and submitted in 2012 at the Department of General History, Dostoevsky Omsk State University, Russia; supervisor: E. N. Efimenko. This is undergraduate coursework, posted as is; the abstract and keywords were added by the translator an...

Replicability of agent-based simulations: a case study with a SEIRS epidemiological model

Reproducibility is not only a cornerstone of the advancement of science, but also of scientific credibility. However, it remains a persistent challenge across many disciplines, and it is now referred to as the “reproducibility crisis.” This issue is particularly relevant in computational modeling. In this paper, we wan...

LLM-based Structured Intermediate Representation for building regulation encoding

Automating the encoding of building codes into formal representations is a critical step for compliance checking, yet it is often hindered by the linguistic complexity of regulations. This paper develops a two-stage pipeline that utilises Large Language Models (LLMs) to generate LegalRuleML (LRML) through a Structured...

Identifying technological problems and exploring potential solutions to support R&D: Tech-mining with multi-LLM applications

The shortening of technology lifecycles and growing technological complexity have made the rapid identification of technical problems and exploration of solutions a critical challenge. Patent analysis can serve as a crucial tool for supporting R&D activities by extracting problem–solution pairs from patent documents. H...

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