Unverified50% confidenceFactExact time
传统大模型天然是无状态的，每次推理都是独立的前向传播过程，没有持久化的外部记忆，也没有与环境交互的接口
1
Sources
50%
Confidence
Long-term
Relevance
7/15/2026
First Seen
Sources
Related Claims
UnverifiedEach inference call to a large model is an independent forward pass; the model weights are completely fixed during inference and there is no mechanism to preserve state across conversation sessions.77% similarPartially VerifiedLarge models are essentially stateless; during each inference, the model can only see the token sequence in the current input and has no persistent memory storage.76% similarVerifiedLarge language models are essentially stateless functions whose weights are fixed at inference time and do not learn over time.73% similarUnverified早期大模型对话是无状态的，模型在推理时仅处理当前输入的token序列，不存在跨请求的内部状态持久化73% similarUnverifiedLarge models are essentially stateless systems that do not remember previous conversations and require an external memory system to achieve coherence in multi-turn dialogues.71% similar
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