Unverified60% confidenceFactExact time
The statelessness of LLMs is a fundamental characteristic of the Transformer architecture; the model stores no state after a session ends or the context is cleared.
2
Sources
60%
Confidence
Long-term
Relevance
7/17/2026
First Seen
Sources
Related Claims
UnverifiedLLM在架构层面采用Transformer的注意力机制,每次推理在当前上下文窗口内独立完成,不存在跨会话的持久化状态77% similarVerifiedThe standard Transformer has no persistent state during inference; every call is a stateless forward computation, and the model itself has no memory capability.75% similarUnverifiedThe current mainstream LLM applications adopt a stateless interaction model, where the model itself does not retain cross-session memory and all context must be temporarily fed in via prompts.73% similarUnverifiedLLM本质上是无状态的文本预测系统,没有感知当前运行环境的原生能力72% similarUnverified大语言模型(LLM)在架构层面是无状态系统,每次推理调用是一次独立的前向传播计算,模型权重在推理阶段完全冻结71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/544308API
curl https://kongchang.com/api/v1/knowledge/claims/544308MCP
get_claim(id=544308)