21 citations · 31 across the 5 of their papers we have counts for
5 papers
The Acquisition of Physical Knowledge in Generative Neural Networks
Luca M. Schulze Buschoff, Eric Schulz, Marcel Binz
As children grow older, they develop an intuitive understanding of the physical processes around them. Their physical understanding develops in stages, moving along developmental t…
Turning large language models into cognitive models
Marcel Binz, Eric Schulz
Large language models are powerful systems that excel at many tasks, ranging from translation to mathematical reasoning. Yet, at the same time, these models often show unhuman-like…
Reinforcement Learning with Simple Sequence Priors
Tankred Saanum, Noémi Éltető, Peter Dayan +2
Everything else being equal, simpler models should be preferred over more complex ones. In reinforcement learning (RL), simplicity is typically quantified on an action-by-action ba…
Meta-in-context learning in large language models
Julian Coda-Forno, Marcel Binz, Zeynep Akata +3
Large language models have shown tremendous performance in a variety of tasks. In-context learning -- the ability to improve at a task after being provided with a number of demonst…
Meta-Learned Models of Cognition
Marcel Binz, Ishita Dasgupta, Akshay Jagadish +3
Meta-learning is a framework for learning learning algorithms through repeated interactions with an environment as opposed to designing them by hand. In recent years, this framewor…