4 papers
Using Probabilistic Programs to Train Inductive Reasoning in Large Language Models
Liyi Zhang, Akshay K. Jagadish, Brenden M. Lake +1
Post-training Large Language Models (LLMs) for reasoning typically focuses on deductive tasks such as mathematics and coding where correctness is verifiable. Yet, many real-world r…
Investigating Concept Alignment Using Implausible Category Members
Sunayana Rane, Brenden M. Lake, Thomas L. Griffiths
Developing AI systems with a human-like understanding of everyday concepts is a key step towards developing safe, reliable systems whose behavior makes sense to humans. When probin…
Are they human? Detecting large language models by probing human memory constraints
Simon Schug, Brenden M. Lake
The validity of online behavioral research relies on study participants being human rather than machine. In the past, it was possible to detect machines by posing simple challenges…
An explainable transformer circuit for compositional generalization
Cheng Tang, Brenden Lake, Mehrdad Jazayeri
Compositional generalization-the systematic combination of known components into novel structures-remains a core challenge in cognitive science and machine learning. Although trans…