Expired50% confidenceFactExact time
There is a positive correlation between the reasoning ability of large language models and the length of the token sequences they output, which academia refers to as the "computational depth hypothesis."
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/4/2026
First Seen
Valid until: 10/2/2026(expired)
Sources
Codex橙皮书:零基础入门AI编程的开源全链路实战指南
bilibili资源汇社区7/2/2026
Related Claims
Verified大型语言模型处理长上下文时,注意力机制的计算复杂度与序列长度的平方成正比78% similarUnverifiedThe inference process of large language models consumes as much computational resources as the training process.78% similarVerifiedThe emergent capability of large language models refers to the complex reasoning ability that suddenly manifests after the parameter scale surpasses a certain threshold.77% similarUnverified大模型擅长语言理解、内容生成和逻辑推理,但在实时信息获取、精确数值计算等方面存在固有局限73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/72405API
curl https://kongchang.com/api/v1/knowledge/claims/72405MCP
get_claim(id=72405)