Unverified50% confidenceFactExact time
A stateful graph persists intermediate results throughout the inference process and feeds intermediate states as inputs to subsequent nodes, which differs from stateless single LLM calls.
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50%
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Long-term
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9/16/2026
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Related Claims
UnverifiedDuring each inference, an LLM only processes the token sequence of the current input and does not retain persistent state across sessions (statelessness).70% similarUnverified在 UnFlow 的实验图谱中，节点代表某次实验的状态（配置与计算结果），边代表从一个状态到另一个状态的转换（改变）69% similarUnverifiedLangGraph combines graph state machines with LLM reasoning, where nodes are tool or LLM calls and edges are conditional transition logic, with a persistence layer (Checkpoint) ensuring that processes can be interrupted and resumed.69% similarUnverified思维链提示有效的原理是：LLM是逐词生成的自回归模型，先生成推理过程可作为后续推断的工作记忆，降低直接跳结论的错误率68% similarUnverified在 LangGraph 中，每个节点执行后返回的字典数据会被合并进全局 State 对象，State 的变化本质上就是状态转换68% similar
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