activity
20242026
most citedComparing the Efficacy of GPT-4 and Chat-GPT in Mental Health Care: A Blind Assessment of Large Language Models for Psychological Support

5 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

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…

cs.HC2025★ 1 cited

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…

cs.SD2025

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…

cs.AI2025★ 2 cited

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…

cs.CL2025★ 1 cited

Language Complexity Measurement as a Noisy Zero-Shot Proxy for Evaluating LLM Performance

Birger Moell, Johan Boye

Large Language Models (LLMs) have made significant strides in natural language generation but often face challenges in tasks requiring precise calculations and structural analysis.…

cs.CL2024

Evaluating Large Language Models with Human Feedback: Establishing a Swedish Benchmark

Birger Moell

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have demonstrated significant capabilities across numerous applications. However, the perform…

cs.CL2024★ 5 cited

Comparing the Efficacy of GPT-4 and Chat-GPT in Mental Health Care: A Blind Assessment of Large Language Models for Psychological Support

Birger Moell

Background: Rapid advancements in natural language processing have led to the development of large language models with the potential to revolutionize mental health care. These mod…