large language models

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

A comprehensive framework for cyberbullying detection that integrates two complementary eXplainable Artificial Intelligence techniques based on Large Language Model explanations and a SHAP value–based interpretability is presented, demonstrating the importance of combining complementary XAI techniques to support transp...

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...

Human-AI Interaction: Evaluating LLM Reasoning on Digital Logic Circuits and the Perception-Correctness Gap

Evaluating three widely used LLMs on 10 undergraduate-level digital logic questions spanning non-standard counters, JK-based state transitions, timing diagrams, frequency division, and finite-state machines suggests that they may be unreliable for core digital logic topics and can inadvertently reinforce misconceptions...

Mapping Artificial Intelligence Research in Aphasia: An AI-Assisted Scoping Review and Semantic Network Analysis

Purpose: A shared view of artificial intelligence (AI) research in aphasia is needed to locate related work across clinical and computing publications. This scoping review mapped research topics and connections, AI method families over time, and reported evaluation and participant characteristics relevant to clinical a...

Decoupled Topological Coprocessing for Mitigating Reasoning Deadlocks and Non-Invasive Trajectory Steering in Large Language Models (DTC v2.0)

Overview We are proud to announce the formal release of Decoupled Topological Coprocessing (DTC v2.0). DTC v2.0 introduces an asynchronous, non-invasive coprocessor architecture that detects and resolves reasoning deadlocks—specifically circular reasoning loops and unanchored extrinsic hallucinations—in Large Reasoning...

Minos: apparatus, parser and per-case captures for "Evaluation harness choices bias the measured tool-use capability of open-weight large language models"

The complete artifact behind the study of harness-induced bias in tool-use evaluation of open-weight large language models: the benchmark apparatus, the model-agnostic multi-dialect call parser, the scorers, every analysis and figure script, and the raw per-case capture logs. The study follows a run-once, re-parse-many...