Unverified50% confidenceSolutionExact time
对大语言模型而言，「不要做X」的负向约束有时比「要做Y」的正向指令更有效，因为负样本相当于在概率空间中设置了禁区
1
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50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
Unverified负向约束通过明确排除不期望的输出收窄概率空间，与正向指令同等重要，可减少模型创造性发挥的偏差74% similarUnverified在代码生成Prompt中，否定性约束（说明不需要什么）能缩小模型搜索空间，比增加期望描述更能提高准确率73% similarUnverifiedPrompt engineering has inherent limitations: the effectiveness of instructions decays over conversation turns (instruction forgetting), and different model versions respond significantly differently to the same instruction.64% similarUnverified当前主流LLM在欧几里得空间推理（如判断两条线段是否相交）上的准确率远低于其在文本推理任务上的表现，这是自回归语言模型架构的固有局限64% similar
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