Unverified50% confidenceFactExact time
LLM以token序列的形式感知世界，而电子表格本质上是二维或多维的关系型结构，模型必须将其展平为线性序列处理，会丢失空间关系信息
1
Sources
50%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
从50%到92%：让AI智能体精通电子表格的实战方法论
Related Claims
UnverifiedUnlike rule-based static analysis tools (such as CodeQL) or symbolic execution tools, LLMs can understand comment intent, recognize the semantics of naming conventions, and infer data flow in the absence of complete type information.69% similarUnverifiedThe essence of LLMs is statistical probability-based sequence prediction rather than true logical reasoning, which creates inherent limitations when handling long-context dependencies, global architectural consistency, and complex edge cases.68% similarUnverifiedLLM可观测性借鉴了传统分布式系统可观测性的三大支柱——日志、指标和追踪，但针对大语言模型的非确定性特征做了适配68% similarUnverifiedLLM本质上是无状态的推理引擎，每次调用模型时所有记忆都必须以文本形式塞入上下文窗口67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/510594API
curl https://kongchang.com/api/v1/knowledge/claims/510594MCP
get_claim(id=510594)