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...

Copenhagen Gender Identity Cohort (KIK): a protocol of a prospective cohort of adults with gender incongruence seeking gender-affirming healthcare.

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...

Attention is All Large Language Model Need

With the advent of the Transformer, the attention mechanism has been applied to Large Language Model (LLM), evolving from initial single- modal large models to today's multi-modal large models. This has greatly propelled the development of ...

Visual Target P3b Amplitude Mediates the Relationship between Childhood Traumatic Experiences and Social Functioning in People at Clinical High Risk for Psychosis.

A new perspective on delusional states: Evidence for claustrum involvement

Delusions are a hallmark positive symptom of schizophrenia, although they are also associated with a wide variety of other psychiatric and neurological disorders. The heterogeneity of clinical presentation and underlying disease, along with...

Deep learning in computational mechanics: a review

Abstract The rapid growth of deep learning research, including within the field of computational mechanics, has resulted in an extensive and diverse body of literature. To help researchers identify key concepts and promising methodologies w...

The Interspeech 2026 NeckVibe Challenge: Voice Disorder Detection via Real-World Monitoring of Neck-Surface Vibration.

The role of white matter microstructure in the association between childhood maltreatment and adult post-traumatic symptoms.

Towards deep learning with segregated dendrites

Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep le...

Modeling Lombard Effects in Voice Disorders Using Daily-Life Monitoring of Ambient Noise and Voice Acoustics.

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...

Automated speech-fluency explanations for schizophrenia diagnosis

Abstract Schizophrenia is a chronic and severe mental disorder that still relies on time-intensive, clinician-administered assessments. Although several automated approaches have been proposed to support diagnosis, these systems often lack ...

Distinct T cell correlates of COVID-19 risk before and after a second booster in previously SARS-CoV-2 infected versus naïve COVAIL trial participants.

A Protein‐Centric Strategy Coupled with Match‐Between‐Run Glycoproteomics Enables Discovery of Robust Site‐Specific Glycan Biomarkers for Hepatocellular Carcinoma

ABSTRACT Dysregulated protein glycosylation is a hallmark of cancer, and systematic investigation of glycosylation patterns is crucial for identifying biomarkers. However, current glycoproteomic studies are constrained by the limited quanti...

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both i...

Human-supervised LLM triage of pig butchering complaints: A validation study of multi-model identifier extraction.

Economic reasoning and artificial intelligence

The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economic...

Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors

Solving long-horizon, temporally-extended tasks using Reinforcement Learning (RL) is challenging, compounded by the common practice of learning without prior knowledge (or tabula rasa learning). Humans can generate and execute plans with te...