5 papers · 1 filter
Simplifying Latent Dynamics with Softly State-Invariant World Models
Tankred Saanum, Peter Dayan, Eric Schulz
To solve control problems via model-based reasoning or planning, an agent needs to know how its actions affect the state of the world. The actions an agent has at its disposal ofte…
Inducing anxiety in large language models can induce bias
Julian Coda-Forno, Kristin Witte, Akshay K. Jagadish +3
Large language models (LLMs) are transforming research on machine learning while galvanizing public debates. Understanding not only when these models work well and succeed but also…
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…
Machine Psychology
Thilo Hagendorff, Ishita Dasgupta, Marcel Binz +5
Large language models (LLMs) show increasingly advanced emergent capabilities and are being incorporated across various societal domains. Understanding their behavior and reasoning…
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…