Unverified60% confidenceFactExact time
Transformer-based LLMs perform an independent forward-pass computation for each inference, with model weights fixed during the inference phase; what is referred to as context memory is essentially the re-injection of historical conversation text into the prompt.
2
Sources
60%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
Hombre：Honcho AI记忆服务器的开源可视化仪表盘
Related Claims
VerifiedLLMs generate text in an autoregressive manner based on the Transformer architecture, predicting only one token per forward pass and then appending that token to the input sequence before predicting the next token.79% similarVerifiedLarge language models are based on the Transformer architecture; each inference is an independent forward propagation process that retains no session state.78% similarUnverifiedLLM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78% similarUnverifiedLLM的预训练本质是在海量文本上进行下一词预测（Next Token Prediction），通过Transformer架构的注意力机制建立词语间语义关联78% similar
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