Academic Articles & Research Papers

A diagnostic hierarchy of epistemic betrayal in large language models

Abstract This paper proposes a hierarchy of epistemic betrayal that distinguishes deceptive behaviors in large language models (LLMs) by the depth at which the infrastructure for epistemic correction is compromised. Drawing on Park et al.’s...

An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...

Specialized Large Language Model for Standardization of Locomotive Maintenance Data

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...

Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions

Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...

HalluciGuard-eye: knowledge graph-enhanced retrieval-augmented generation for hallucination detection and mitigation in ophthalmic multimodal large language models.

Addressing benchmarking gaps in large language models for health and medicine with dynamic red-teaming.

Simulating a virtual tumor board with large language models: a pilot study in NSCLC patients receiving immunotherapy.

An Exploratory Study: Can Vision-Enabled Large Language Models Interpret Selected Static Urologic Images?

Context-Aware LLM-Guided Neighbourhood Search for Simulation-Based Production Scheduling

The paper presents a novel large language model-based neighbourhood search method for production scheduling using discrete-event simulation (DES) as the modelling and evaluation engine. The combination of large language models (LLMs) and DE...

Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning ...

Teens, Tech, and Talk: Adolescents’ Use of and Emotional Reactions to Snapchat’s My AI Chatbot

Due to technological advancements such as generative artificial intelligence (AI) and large language models, chatbots enable increasingly human-like, real-time conversations through text (e.g., OpenAI’s ChatGPT) and voice (e.g., Amazon’s Al...

Employing General-Purpose and Biomedical Large Language Models with Advanced Prompt Engineering for Pharmacoepidemiologic Study Design.

Expert Agents for Social and Emotional Learning: An Agentic Graph Retrieval Augmented Generation Approach

The positive impact of Social and Emotional Learning (SEL) activities in schools is widely recognized in various sectors, including mental health, social relationships, and academic performance of students. This impact can be efficiently re...

Artificial intelligence and increasing misinformation

With the recent advances in artificial intelligence (AI), patients are increasingly exposed to misleading medical information. Generative AI models, including large language models such as ChatGPT, create and modify text, images, audio and ...

The Effects of Large Language Models on the Generation of Multiple-choice Questions in Medical Education: A Scoping Review

Background: Constructing high-quality multiple-choice questions (MCQs) is critical yet resource-intensive in medical education. Large language models (LLMs), such as ChatGPT, have become promising tools for generating MCQs in medical educat...

Assisting Screening of Adolescent Depression With Large Language Models as Symptom Detectors: Algorithm Development and Validation.

Large language model bias auditing for periodontal diagnosis using an ambiguity-probe methodology: a pilot study

BackgroundLarge Language Models (LLMs) in healthcare holds immense promise yet carries the risk of perpetuating social biases. While artificial intelligence (AI) fairness is a growing concern, a gap exists in understanding how these models ...

Evaluating Artificial Intelligence’s Role in Developing Research Questions in Head and Neck Reconstruction

Summary:. Generative artificial intelligence (AI) large language models are an emerging technology, with ChatGPT and Gemini being 2 well-known examples. The current literature discusses clinical applications and limitations of AI, but its r...

Accuracy and reliability of Manus, ChatGPT, and Claude in case-based dental diagnosis

IntroductionArtificial intelligence (AI), particularly large language models (LLMs), is transforming healthcare education and clinical decision-making. While models like ChatGPT and Claude have demonstrated utility in medical contexts, thei...