Unverified50% confidenceFactExact time
Context drift differs from model hallucination: hallucination is a factual error within a single generation, whereas drift is a deviation that accumulates gradually across sessions or long reasoning chains.
1
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50%
Confidence
Long-term
Relevance
10/19/2026
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Related Claims
UnverifiedHallucinated proofs differ from rounding errors in numerical computation or obvious error reports in symbolic computation, as the latter two tend to be exposed in subsequent steps, whereas hallucinated proofs may remain undetected until discovered by peer review.77% similarUnverified模型规模越大，幻觉的表述往往越流畅、越具迷惑性，识别难度反而上升76% similarVerifiedLLMs may make incorrect judgments due to hallucinations, prompt injection, or contextual misunderstanding, and without independent verification mechanisms, faulty reasoning can directly translate into erroneous production operations74% similarVerifiedResearch indicates that hallucination rates do not have a linear negative correlation with model scale, and larger models sometimes produce harder-to-detect misinformation in a more fluent manner.74% similarUnverifiedExisting hallucination mitigation approaches (corpus grounding, mutual verification, preference alignment) mostly treat hallucinated terms as generic noise and filter them using consistency heuristics, lacking mechanistic explanations and principled criteria for determining how many expansion terms to retain.74% similar
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