The Digital Press

A recent paper from Arizona State University argues that chain-of-thought (CoT) reasoning in small language models is just pattern memorization, not genuine reasoning, but this critique suggests the paper oversimplifies and overgeneralizes.

Why it matters: The paper challenges whether AI models truly reason or just mimic learned patterns, impacting AI interpretability and trust.

The big picture: Genuine reasoning likely involves complex language use and large models; small toy models can’t capture true reasoning dynamics.

The other side: Human reasoning is also imperfect, heuristic-driven, and context-dependent, so AI’s “mirage” may mirror human cognitive limits.

Commenters say: They appreciate the nuanced critique of the paper’s narrow approach and urge clearer definitions of “real” reasoning in AI research.