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cs.CL2026
Thought without systematicity? Evaluating reasoning models on rule induction tasks
Simon Schug, Brenden M. Lake
A central tenet of human cognition is systematicity, the principle that understanding one concept is inherently tied to understanding close variations of that concept. Do reasoning…
cs.CL2026
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…
cs.CL2026
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…