Unverified50% confidenceFactExact time
Jason Wei proposed the Chain-of-Thought Prompting method, which has had a profound influence on current LLM research.
1
Sources
50%
Confidence
Long-term
Relevance
10/7/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe Chain-of-Thought prompting paper published in 2022 by Jason Wei et al. of Google Brain was the first to systematically demonstrate that adding step-by-step reasoning examples significantly improves the accuracy of large models such as PaLM on mathematical reasoning tasks70% similarUnverifiedChain-of-Thought (CoT), proposed by Wei et al., improves accuracy on complex mathematical and logical reasoning tasks by guiding the model to display its reasoning process step by step.69% similarVerifiedChain-of-thought reasoning was proposed by Wei et al. in 2022, referring to guiding a model to output step-by-step intermediate reasoning processes before giving a final answer68% similarUnverifiedThe introduction of Chain-of-Thought prompting in 2022 enabled LLMs to perform step-by-step reasoning.67% similarUnverifiedThe study analyzed the correlation between protocol-specific characteristics (complexity, number of states, clarity of transition logic) and LLM reasoning performance.66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/982751API
curl https://kongchang.com/api/v1/knowledge/claims/982751MCP
get_claim(id=982751)