Unverified50% confidenceFactExact time
The model is stateless, and the entire conversation is resent with each call, so understanding the mechanism helps save tokens.
1
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50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
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Related Claims
VerifiedLarge models are essentially stateless, and multi-turn conversations are implemented by sending the historical conversation records together with each request to the model.76% similarVerifiedEach 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.75% similarUnverifiedWhen a model becomes confused during a multi-turn conversation, stopping the conversation, clearing the context, and consolidating all known information into a single complete single-turn instruction yields noticeably better model performance.74% 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74% similarUnverifiedA traditional large model is essentially a stateless function; every conversation starts from scratch, and context is truncated once it exceeds the context window length limit.74% similar
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