6 papers · 1 filter
Generating Computational Cognitive Models using Large Language Models
Milena Rmus, Akshay K. Jagadish, Marvin Mathony +2
Computational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models…
Automated scientific minimization of regret
Marcel Binz, Akshay K. Jagadish, Milena Rmus +1
We introduce automated scientific minimization of regret (ASMR) -- a framework for automated computational cognitive science. Building on the principles of scientific regret minimi…
Centaur: a foundation model of human cognition
Marcel Binz, Elif Akata, Matthias Bethge +37
Establishing a unified theory of cognition has been a major goal of psychology. While there have been previous attempts to instantiate such theories by building computational model…
Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
Can Demircan, Tankred Saanum, Akshay K. Jagadish +2
In-context learning, the ability to adapt based on a few examples in the input prompt, is a ubiquitous feature of large language models (LLMs). However, as LLMs' in-context learnin…
Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks
Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann +2
Ecological rationality refers to the notion that humans are rational agents adapted to their environment. However, testing this theory remains challenging due to two reasons: the d…
In-context learning agents are asymmetric belief updaters
Johannes A. Schubert, Akshay K. Jagadish, Marcel Binz +1
We study the in-context learning dynamics of large language models (LLMs) using three instrumental learning tasks adapted from cognitive psychology. We find that LLMs update their…