Unverified50% confidenceFactExact time
现代ASR模型在解码每个词时会计算概率分布，模型识别越有把握置信度分数越接近1.0
1
Sources
50%
Confidence
Long-term
Relevance
8/24/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWhen generating each token, large language models perform probabilistic sampling over all possible next words in the vocabulary, rather than deterministically selecting a unique answer.73% similarUnverifiedLarge language models can approximately estimate decision confidence by analyzing token probability distributions, explicitly outputting self-evaluation scores, or observing answer consistency across multiple samplings.73% similarVerifiedThe core principle of large models is probabilistic text continuation, and the output is probabilistic sampling rather than deterministic output.71% similarVerifiedThe essence of large language models is learning the conditional probability distribution of what the next word is given the preceding text71% similarUnverified用户输入的每个词都会成为模型的上下文，改变模型接收到的数学输入，进而影响解码阶段的概率分布和输出内容70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/794210API
curl https://kongchang.com/api/v1/knowledge/claims/794210MCP
get_claim(id=794210)