Unverified50% confidenceFactExact time
LLM虽然不直接输出归一化概率向量，但可通过多种工程手段近似估计决策置信度
1
Sources
50%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
AI Agent人在回路（HITL）设计：风险分级与最佳实践
Related Claims
UnverifiedLLM可通过分析输出token的对数概率分布、思维链末尾自我评估、温度采样统计答案分布熵值等手段近似估计决策置信度79% similarVerifiedAn LLM is essentially a statistical probability model that predicts the most likely next token rather than truly understanding business semantics.78% similarVerifiedLLMs generate output token by token in an autoregressive manner, with each word's selection based on probability sampling from the current context.78% similarPartially VerifiedLLMs use an autoregressive generation mechanism, sampling the next token at each step based solely on a probability distribution.78% similarUnverifiedThe essence of LLMs is statistical probability-based sequence prediction rather than true logical reasoning, which creates inherent limitations when handling long-context dependencies, global architectural consistency, and complex edge cases.77% similar
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