large language models

Reproducibility Package for Comparative Evaluation of Lexical Machine Learning, CodeBERT Fine-Tuning, Prompt-Based LLMs, and Retrieval-Augmented Generation for SATD Detection

This archive contains the reproducibility package for the manuscript titled “Comparative Evaluation of Lexical Machine Learning, CodeBERT Fine-Tuning, Prompt-Based Large Language Models, and Retrieval-Augmented Generation for Self-Admitted Technical Debt Detection.” The package includes the executed notebook, source co...

The Standard Model Carrier Exhaustion Closure

Primitive Closure, Skin Openness, BSM Audit, and No Same-Scope Primitive Escape This paper completes the Standard Model carrier-exhaustion sequence. It asks whether any same-scope Standard Model-associated attribute retains primitive standing outside the certified carrier package after the gauge, matter, charge, coupli...

Dataset for: Beyond the Tailpipe: A Critical Review of Competing Visions of Net Zero Transport

This dataset contains the search record, screening decisions, model prompts and data extraction matrix for the critical review titled "Beyond the Tailpipe: A Critical Review of Competing Visions of Net Zero Transport." The review is a critical review conducted as a critical interpretive synthesis. It examines how the l...

Writing is thinking: toward a neuropsychological model of scientific writing as knowledge construction

Scientific writing has historically been conceptualized as a communicative act—the registration of knowledge elaborated through independent cognitive processes. This article challenges that assumption and proposes that scientific writing constitutes an active neurocognitive system of knowledge construction and a privil...

Leakage-Aware LLM Augmentation for Attrition Prediction: A DecisionCentric Evaluation

A leakage-aware, dual-network augmentation framework that integrates the semantic reasoning of Large Language Models with the distributional rigorousness of GAN discriminators is proposed, offering HR practitioners a robust, decision-centric tool to identify at-risk employees without sacrificing transparency.

Interpretable speech biomarkers of psychological resilience in major depressive disorder via expert-guided large language models

This framework successfully decodes cognitive coping strategies independent of depressive mood, providing potentially actionable targets for personalized psychiatric interventions and a promising, interpretable digital biomarker for psychological resilience.

Exploring young adult cancer survivors’ perspectives on generative AI chatbots for symptom support

Abstract Background Young adult cancer survivors (ages 18–39) often experience persistent treatment-related symptoms that negatively affect daily functioning, psychosocial well-being, and quality of life, yet report unmet educational needs for symptom management. Generative artificial intelligence (AI) technologies, su...

Benchmarking Stylometric Metrics for AI Authorship Verification: A Glass-Box Forensic Framework Across Language Models

Assessing AI-generated academic writing in Spanish: a multivariate analysis of syntactic variation across ChatGPT, Gemini, and Claude

Findings indicate that the ChatGPT, Gemini, and Claude models generate academic Spanish through differentiated syntactic configurations, suggesting that dependency-based syntactic profiling can support the interpretation of AI-assisted academic writing, inform rubric refinement for academic Spanish, and provide transpa...

The Use of Large Language Models (LLMs) in the Automatic Generation of GIS Workflows: The Case of the LiNaAssistant Plugin for QGIS

Artificial Intelligence in Geospatial Data Processing and Analysis -> Knowledge representation and geospatial data handling with Multimodal Language Models and Agentic Systems

TOMAgent: Budget-Aware Test Opportunity Modeling for Reliability-Oriented Multi-Agent Unit Test Generation

Frontier AI as Strategic Infrastructure: Sovereign Governability Under Dependency

When personal data enters an artificial-intelligence development lifecycle, deleting the original record may not end the consequences of an unlawful, deceptive, or otherwise prohibited data practice. The data may have informed a model, algorithm, embedding, feature set, evaluation corpus, or other operational artifact....