7 papers
What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces
Birger Moëll
What makes writing "good" remains a persistent question in literary studies and computational linguistics. We present a two-study investigation of how reasoning-enabled LLMs evalua…
Medical Reasoning in LLMs: An In-Depth Analysis of DeepSeek R1
Birger Moell, Fredrik Sand Aronsson, Sanian Akbar
Integrating large language models (LLMs) like DeepSeek R1 into healthcare requires rigorous evaluation of their reasoning alignment with clinical expertise. This study assesses Dee…
Artificial Humans
Birger Moell
This study investigates the development and assessment of an artificial human designed as a conversational AI chatbot, focusing on its role as a clinical psychologist. The project…
The order in speech disorder: a scoping review of state of the art machine learning methods for clinical speech classification
Birger Moell, Fredrik Sand Aronsson, Per Ãstberg +1
Background:Speech patterns have emerged as potential diagnostic markers for conditions with varying etiologies. Machine learning (ML) presents an opportunity to harness these patte…
Voice Cloning for Dysarthric Speech Synthesis: Addressing Data Scarcity in Speech-Language Pathology
Birger Moell, Fredrik Sand Aronsson
This study explores voice cloning to generate synthetic speech replicating the unique patterns of individuals with dysarthria. Using the TORGO dataset, we address data scarcity and…
Large Language Models and Mathematical Reasoning Failures
Johan Boye, Birger Moell
This paper investigates the mathematical reasoning capabilities of large language models (LLMs) using 50 newly constructed high-school-level word problems. Unlike prior studies tha…