49 citations · 61 across the 10 of their papers we have counts for
10 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…
Shaping Shared Languages: Human and Large Language Models' Inductive Biases in Emergent Communication
Tom Kouwenhoven, Max Peeperkorn, Roy de Kleijn +1
Languages are shaped by the inductive biases of their users. Using a classical referential game, we investigate how artificial languages evolve when optimised for inductive biases…
Searching for Structure: Investigating Emergent Communication with Large Language Models
Tom Kouwenhoven, Max Peeperkorn, Tessa Verhoef
Human languages have evolved to be structured through repeated language learning and use. These processes introduce biases that operate during language acquisition and shape lingui…
What does Kiki look like? Cross-modal associations between speech sounds and visual shapes in vision-and-language models
Tessa Verhoef, Kiana Shahrasbi, Tom Kouwenhoven
Humans have clear cross-modal preferences when matching certain novel words to visual shapes. Evidence suggests that these preferences play a prominent role in our linguistic proce…
The Curious Case of Representational Alignment: Unravelling Visio-Linguistic Tasks in Emergent Communication
Tom Kouwenhoven, Max Peeperkorn, Bram van Dijk +1
Natural language has the universal properties of being compositional and grounded in reality. The emergence of linguistic properties is often investigated through simulations of em…
Is Temperature the Creativity Parameter of Large Language Models?
Max Peeperkorn, Tom Kouwenhoven, Dan Brown +1
Large language models (LLMs) are applied to all sorts of creative tasks, and their outputs vary from beautiful, to peculiar, to pastiche, into plain plagiarism. The temperature par…
EduGym: An Environment and Notebook Suite for Reinforcement Learning Education
Thomas M. Moerland, Matthias Müller-Brockhausen, Zhao Yang +7
Due to the empirical success of reinforcement learning, an increasing number of students study the subject. However, from our practical teaching experience, we see students enterin…
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…