Response: Emergent analogical reasoning in large language models (2308.16118v2)

Abstract: In their recent Nature Human Behaviour paper, "Emergent analogical reasoning in LLMs," (Webb, Holyoak, and Lu, 2023) the authors argue that "LLMs such as GPT-3 have acquired an emergent ability to find zero-shot solutions to a broad range of analogy problems." In this response, we provide counterexamples of the letter string analogies. In our tests, GPT-3 fails to solve simplest variations of the original tasks, whereas human performance remains consistently high across all modified versions. Zero-shot reasoning is an extraordinary claim that requires extraordinary evidence. We do not see that evidence in our experiments. To strengthen claims of humanlike reasoning such as zero-shot reasoning, it is important that the field develop approaches that rule out data memorization.