Unverified50% confidenceCautionExact time
Graph construction itself relies on the LLM correctly extracting nodes and edge relations, and extraction errors may propagate to subsequent decisions.
1
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50%
Confidence
Long-term
Relevance
10/20/2026
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Related Claims
UnverifiedHaving LLMs holistically reason about causal structure in a larger context (Rowwise or Full graph) tends to produce better results than making isolated pairwise judgments.74% similarUnverifiedLLM往往能在代码第一行就输出整个解法中最关键的设计决策,这种从结论向过程展开的线性输出特征与人类工程师探索性、增量修正的认知过程存在本质差异72% similarUnverifiedLLM在「生成」和「评估」时激活的推理路径不同,生成任务偏向延续已有语义方向,评估任务激活更多批判性、面向异常检测的推理路径71% similarUnverifiedThe implications for LLM engineering practice include: do not directly treat the probabilities output by the model as decision confidence; in scenarios where handoff to a human is not possible, a conservative fallback strategy should be explicitly designed; threshold selection requires statistical guarantees.71% similarUnverifiedLLMs' probability judgments drift under the influence of irrelevant factors such as how evidence is framed and the order in which it is presented.71% similar
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