Unverified60% confidenceFactExact time
Large language models are essentially stateless, and code repositories, as external persistent storage, compensate for this deficiency.
2
Sources
60%
Confidence
Long-term
Relevance
7/24/2026
First Seen
Sources
Related Claims
UnverifiedEven when large language models support a 200K token context, they exhibit the Lost in the Middle phenomenon when processing large codebases, meaning their attention to earlier information in the context decreases progressively.71% similarUnverifiedDuring the decoding process of masked diffusion language models, once a token is committed to a masked position it is generally irreversible and cannot be corrected.71% similarUnverifiedLarge language models are essentially stateless functions, and a model's memory depends entirely on the content within the context window.69% similarUnverifiedLarge language models have no persistent memory across sessions, and any information outside the context window is invisible to them; character cards solve the problem of character drift by packaging character information into fixed entries injected along with the prompt.69% similarUnverifiedThe "forgetfulness" of large language models stems from their stateless inference architecture: each time the API is called, the model only processes the token sequence passed in the current request and retains no internal state across requests.69% similar
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