Unverified50% confidenceSolutionExact time
Deterministic orchestration demotes the model to a stateless function call that receives only the current sub-problem and returns structured output, holding no cross-round memory.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
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Related Claims
VerifiedConstrained decoding forces the model to produce output conforming to a preset structure by masking out tokens that do not comply with the target grammar or schema at each generation step.75% similarUnverifiedPrompt caching reuses input processing, not model output or memory; each request is still a stateless, independent inference.74% similarVerifiedLarge models are essentially stateless; during each inference, the model can only see the token sequence in the current input and has no persistent memory storage.74% similarUnverifiedBecause the Tic-Tac-Toe training data covers all possible states, the model's learning task degenerates into a memorization task with no out-of-distribution issues, and the compounding error problem of behavioral cloning naturally dissolves.73% similarUnverifiedWhen parsing model output, the parsing logic should be wrapped with try...except, and an empty list should be returned if parsing fails, to ensure the program does not crash.73% similar
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