large language models

Automated surveillance of primary outcome reporting in clinical trials: Development and validation of a scalable screening pipeline.

Background: Detecting discrepancies between registered and published trial outcomes currently requires manual expert review, limiting surveillance to small samples. No scalable automated system exists for continuous monitoring of outcome reporting integrity across the clinical trial literature. We aimed to develop and...

Large language models in STEM education: Opportunities, pedagogical shifts, ethical concerns, and future research directions

From Fabricated Citations to Unverified Journal Matches: Problems and Solutions in LLM Assisted Manuscript Generation

Examining scopus-jurnal, an open-source Python multi-agent pipeline that retrieves literature, drafts IMRaD sections, validates citations, reviews manuscripts, and recommends journals, shows that although the pipeline abstained when evidence was absent, weaknesses emerged between LLM outputs and deterministic code.

Adapting large language models for urban trip purpose inference: A domain-informed textual representation and fine-tuning framework

VirtuAI-Safe: Personalized Situated Safety Learning through Integration of VR and LLMs

Construction safety outcomes are strongly shaped by human factors, including how individuals perceive hazards, interpret contextual cues, and make safety-related decisions in dynamic work environments. Safety education therefore plays a critical role in preparing future construction professionals to reason about risk...

Mind the mismatch: mapping stakeholder-interest divergence in urban e-mobility across major western anglophone arenas using large language models

Building Code Question-Answering Systems Enhanced by Large Language Models and Knowledge-Graph-Based Retrieval-Augmented Generation

A retrieval-augmented generation system enhanced with a knowledge graph to interpret building codes by leveraging both the semantic content and structural relationships within the documents by leveraging both the semantic content and structural relationships within the documents.

Capability Generalization in Privileged-Execution LLM Agents: A Catalog of Unanticipated Behaviors During Autonomous Network Defense

Large language models are increasingly proposed as autonomous network-defense agents, which requires privileged command execution not scoped to their stated objective. Evaluating a multi-agent LLM framework that proposes, implements, and validates mitigations against replayed adversary emulation, we observed agents exc...

Explainable AI-Driven Intelligent Video Summarization for Next-Generation Video Production and Content Management

This chapter reviews the development of video summarisation using handcrafted features and deep learning models, the recent advances in transformer-based, vision-language, multimodal learning, and large language models for video summarisation. It introduces the main steps of the summarization pipeline: keyframes extrac...

Can candidates trust a confident answer? Free and paid large language models on dental specialty examination questions

Response-level dataset and analysis code for a study of stated confidence and repeated-query consistency in seven large language models answering the oral and maxillofacial radiology questions of the Turkish Dental Specialty Examination (DUS), 2012–2026. Seven models from four vendors, including three pairs available a...

Managing Vector Data for Retrieval Augmented Generation@Dagstuhl Seminar Summary

This report summarizes discussions that took place in the context of a Dagstuhl seminar1 to explore the emerging paradigm of AI-native databases designed to support agentic workflows and Retrieval-Augmented Generation (RAG) by integrating Large Language Models (LLMs) with robust database abstractions. The central synth...

Adaptive Learning and Collaborative Self-Adaptive Learning Between Self-and-Interaction Models: A Unified Framework for Adaptive Mode Switching

Learning systems often face a fundamental design choice between adapting independently and adapting through collaboration. Independent adaptation allows a model to preserve its autonomy, exploit its own experience, and avoid unnecessary coordination costs. Collaborative adaptation allows multiple models to exchange inf...