Thought without systematicity? Evaluating reasoning models on rule induction tasks
Study finds reasoning models often fail on structurally equivalent variants of tasks they solve, suggesting their reasoning lacks systematicity.
The paper extends rule induction tasks from cognitive science using task isomorphisms such as recombination and substitution to test systematicity in reasoning models. Despite solving tasks correctly, models frequently fail on structurally equivalent variants of the same task. The authors conclude many model behaviors lack systematicity, making it difficult to establish cognitive abilities beyond the specific evaluation contexts.
- Extends cognitive-science rule induction tasks via isomorphisms like recombination and substitution
- Models that solve a task often fail structurally equivalent variants
- Questions robustness of claimed reasoning abilities in current models
From the original article
1 min read at huggingface.co
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 models robustly exhibit such systematicity? If so, we would expect consistent performance on structurally equivalent variants of the same task.
By Simon Schug, Brenden M. Lake · huggingface.co
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.