large language models

AI-assisted data extraction for systematic reviews in education

Kinship Reasoning as a Testbed for Neuro-Symbolic Architectures: Comparing LLM–Prolog Integration Strategies and Assessing Cultural Bias

Research on AI-Empowered Software Test Case Generation

This work leverages large language models to analyze and extract test cases from requirement documents, and constructs an automated test case generation framework by specifying standard input and output values of test samples, test coverage scope, and AI agent roles.

Uncoded Clinical Features from Multilingual Electronic Health Records in Catalonia: Development and Validation Study (Preprint)

BACKGROUND Unstructured free‑text narratives in electronic health records (EHRs) contain critical clinical information that is not captured by structured standard codes. In Catalonia, primary care notes follow a semi‑structured format known as MEAP (in Catalan). However, extracting structured variables using cloud‑host...

M3: Conversational LLMs simplify secure clinical data access, understanding, and analysis

Large-scale clinical databases offer opportunities for medical research, but their complexity creates barriers to effective use. The Medical Information Mart for Intensive Care (MIMIC-IV), one of the world’s largest open-source electronic health record databases, traditionally requires both SQL proficiency and clinical...

Vision Based Fitness Analysis and Adaptive Health Management Using Deep Learning and Large Language Models

In the past few years, a growing understanding of health and fitness has highlighted the need for intelligent systems that offer personalized and adaptive recommendations. This work describes a vision-based fitness analysis and adaptive health management system that utilizes computer vision and generative artificial in...

ChatGear: an artificial intelligence system for gear transmission design based on large language models

A hybrid framework combining large language models and Shapley-based methods for explainable cyberbullying detection

Cyberbullying remains a pervasive threat across social media platforms, highlighting the need for reliable detection systems and transparent decision-making processes. This work presents a comprehensive framework for cyberbullying detection that integrates two complementary eXplainable Artificial Intelligence (XAI) tec...

Toward agentic large language models in travel behavior research

SRMP-S: Self-Refining Multi-Planner Strategy for Long-Horizon Robotic Tasks

Enabling robotic agents to perform complex long-horizon tasks has been a long-standing goal in robotics and artificial intelligence (AI). Existing Large Language Models (LLMs)-based symbolic planners auto-generate Planning Domain Definition Language (PDDL) specifications to bridge language and formal reasoning, but the...

THE GLOBAL EVIDENCE ENGINE / From Silent Collapse to a Living Scientific Base / FIELD COMPUTE / AMOC Atlas, Guide and Field Compute Companion : Observational Methods, Diagnostics, Prospective Validation and Reproducible Research Software

FIRST PARTIAL RELEASE OF PROJECT FILES 14th September 2026AMOC · SIEVE · MAC · FIELD COMPUTE · SILENT COLLAPSE THE GLOBAL EVIDENCE ENGINE From Silent Collapse to a Living Scientific Base A connected research package for observing, representing, testing, challenging, and reproducing scientific claims about a changing Ea...

A trait-based persuasive framework for preference elicitation by social assistive robot

Human preferences are often ill-defined and shaped by contextual and situational factors, posing challenges for effective human–robot interaction. Social Assistive Robots can address this by employing adaptive, context-aware persuasive strategies to better elicit user preferences and support healthier behaviors. In thi...