Unverified70% confidenceFactExact time
Scaling laws were formally proposed by OpenAI researchers Kaplan et al. in 2020 in the paper "Scaling Laws for Neural Language Models".
2
Sources
70%
Confidence
Long-term
Relevance
7/15/2026
First Seen
Sources
Related Claims
VerifiedScaling Laws were first systematically proposed and quantified by OpenAI researchers in the 2020 paper "Scaling Laws for Neural Language Models."84% similarVerifiedIn 2020, OpenAI researchers Kaplan et al. published a paper that first systematically revealed the predictable power-law relationships between language model performance and model parameter count, training data volume, and computational budget (Scaling Law)83% similarUnverified2020年OpenAI的Kaplan等人论文首次系统证明神经网络性能与模型参数量、训练数据量、计算量之间存在幂律关系69% similarUnverifiedTogetherAI 在 2024 年发表研究论文将集成学习思路引入大语言模型领域，实验表明将多个开源模型输出交由聚合模型综合处理后结果可超越任何单一模型59% similarUnverifiedThe Feynman learning method holds that the hallmark of truly understanding a concept is the ability to explain it clearly to others in simple language.57% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/518786API
curl https://kongchang.com/api/v1/knowledge/claims/518786MCP
get_claim(id=518786)