Unverified50% confidenceFactExact time
SKIM (Self-Keyed In-Parameter Memorization) is a closed-form method that writes conversation content directly into the parameters of a frozen language model, enabling the model to answer questions about past conversations using its parameters alone.
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Long-term
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10/28/2026
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Related Claims
UnverifiedChat templates are the rule layer by which inference frameworks convert multi-turn conversations, system prompts, and tool call sequences into model input tokens, usually distributed as Jinja2 templates together with the model weights.66% similarVerifiedConversational memory is stored in the form of memory summaries, which can become skewed as conversations grow, whereas global personalization instructions are hard-coded into the system prompt of every request and are not affected by memory degradation.64% similarUnverifiedLarge language models themselves are stateless, and each request is an independent computation; so-called 'remembering' usually relies on two mechanisms: one is concatenating historical conversation into the current prompt (the context window), and the other is retrieval-augmented generation (RAG) through external storage (such as vector databases or file systems).64% similarUnverifiedCache Read refers to the model directly reading intermediate computation results of already-parsed context from cache during multi-turn conversations or repeated calls, without needing to reprocess.63% similarUnverifiedPrefill is the first stage of large language model inference, in which the model reads the entire prompt entered by the user in one pass and computes key-value vectors for each token and stores them in VRAM.63% similar
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