Unverified50% confidenceFactExact time
Typed questions pre-declare the value space of the answer, letting the model output only a normalized probability distribution, thereby eliminating parsing errors, format drift, and hallucinations.
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10/12/2026
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VerifiedExplicitly instructing the model via prompt to answer only based on the provided context and to respond with "I don't know" if the answer is not present can mitigate hallucination (grounding).75% similarUnverifiedThe Adjudicated Query pattern externalizes judgment logic to a deterministic rules engine, thereby avoiding the problems of approximate matching in vector retrieval and the non-reproducibility of probabilistic sampling in LLMs.74% similarUnverifiedOutput examples are key to suppressing randomness and hallucinations in large models: without examples responses may be irregular, but once a formatted reference is provided the output will closely follow the expected template.73% similarVerifiedThe hallucination problem in large language models stems from their nature as statistical probability-based sequential prediction systems, where generated tokens are based on conditional probability maximization rather than genuine logical reasoning.72% similar
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