Verified65% confidenceOpinionTime unknown
Incremental Prompting can reduce hallucinations and logical errors in large language models when processing complex instructions
3
Sources
65%
Confidence
Long-term
Relevance
6/3/2026
First Seen
Sources
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Unverified利用diff而非全文替换来驱动代码修改可减少token消耗并降低模型幻觉引发大范围错误的风险79% similarUnverifiedLarge language models are prone to hallucinations when handling complex and ambiguous requirements; the larger and more ambiguous the scope, the higher the probability of AI errors, so reducing scope for MVP lowers the risk of AI mistakes.77% similarUnverifiedProviding reference text, constraining output boundaries, and guiding reasoning steps can reduce the probability of large-model hallucination, but cannot completely avoid it.77% similarUnverifiedLarge language models are prone to hallucination drift when handling detail consistency problems that require precise long-range context tracking.76% similar
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