Unverified50% confidenceFactExact time
In RLM, input P exists solely as a REPL variable (context/ctx) and never appears in the root LLM's window; the root LLM only receives small-volume metadata messages
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/11/2026
First Seen
Valid until: 1/9/2027
Sources
Related Entities
Related Claims
UnverifiedThe RLM REPL provides helper functions: context_meta() returns restricted metadata, peek(start, end) retrieves a bounded slice by offset, search(pattern, max_hits=100) performs regex search with a hit cap, and sub_query(prompt, slice) delegates semantic judgment to a sub-LLM69% similarUnverifiedThe RLM system prompt specifies that the model is the root node of a recursive language model, that input is loaded into a long-running Python REPL, and that the model only receives a real-time context handle rather than the raw content67% similarUnverifiedDuring each inference, an LLM only processes the token sequence of the current input and does not retain persistent state across sessions (statelessness).65% similarPartially VerifiedEach LLM inference is stateless and constrained by the limited context window; the model has no persistent memory of its own.65% similarUnverifiedThere is no module inside an LLM dedicated to storing 'feelings' or 'states'; every output is the result of a conditional probability calculation over the input prompt.60% similar
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