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20242026
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cs.LG2026

metabeta -- A fast neural model for Bayesian mixed-effects regression

Alex Kipnis, Marcel Binz, Eric Schulz

Hierarchical data with multiple observations per group is ubiquitous in empirical sciences and is often analyzed using mixed-effects regression. In such models, Bayesian inference…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

Evaluating alignment between humans and neural network representations in image-based learning tasks

Can Demircan, Tankred Saanum, Leonardo Pettini +5

Humans represent scenes and objects in rich feature spaces, carrying information that allows us to generalise about category memberships and abstract functions with few examples. W…

cs.LG2024

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…

cs.LG2024

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…