7 citations · 11 across the 5 of their papers we have counts for
5 papers
Seeking Information with RAG-Assistants: Does Model Size Matter in Human-AI Collaborations?
Lennard C. Froma, Tom Kouwenhoven, Maaike H. T. de Boer +2
Much research on LLMs has focused on increasing benchmark performance. However, the evaluation of such models in real-world collaborative human-AI workflows has stayed behind. This…
Traces of Social Competence in Large Language Models
Tom Kouwenhoven, Michiel van der Meer, Max van Duijn
The False Belief Test (FBT) has been the main method for assessing Theory of Mind (ToM) and related socio-cognitive competencies. For Large Language Models (LLMs), the reliability…
ChiSCor: A Corpus of Freely Told Fantasy Stories by Dutch Children for Computational Linguistics and Cognitive Science
Bram M. A. van Dijk, Max J. van Duijn, Suzan Verberne +1
In this resource paper we release ChiSCor, a new corpus containing 619 fantasy stories, told freely by 442 Dutch children aged 4-12. ChiSCor was compiled for studying how children…
Theory of Mind in Large Language Models: Examining Performance of 11 State-of-the-Art models vs. Children Aged 7-10 on Advanced Tests
Max J. van Duijn, Bram M. A. van Dijk, Tom Kouwenhoven +3
To what degree should we ascribe cognitive capacities to Large Language Models (LLMs), such as the ability to reason about intentions and beliefs known as Theory of Mind (ToM)? Her…
Large Language Models: The Need for Nuance in Current Debates and a Pragmatic Perspective on Understanding
Bram M. A. van Dijk, Tom Kouwenhoven, Marco R. Spruit +1
Current Large Language Models (LLMs) are unparalleled in their ability to generate grammatically correct, fluent text. LLMs are appearing rapidly, and debates on LLM capacities hav…