Unverified50% confidenceFactExact time
Probabilistic provenance labeling means platforms display continuous or multi-dimensional signals such as synthesis probability, generative model type, and provenance credential status, rather than simply labeling content as "true" or "false".
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe probability figures provided by guided generative models are essentially 'well-constrained inferences' rather than directly verifiable truths.73% similarUnverified生成式AI基于概率预测下一个token生成内容，而非从数据库检索真实事实，因此可能生成看似真实但不存在的法律判例71% similarUnverified循环论证偏差指当特征本身隐含标签信息时模型看似准确率极高实则用答案预测答案67% similarUnverifiedThe confidence output of large language models is fundamentally a product of probability distributions rather than a genuine judgment of factual truth or falsehood, and may express high confidence in incorrect statements.66% similarUnverifiedLarge models rely on a pseudorandom number generator as the sampling source when generating text, and if that pseudorandom source can be predicted, the generation process no longer possesses true unpredictability.66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1034297API
curl https://kongchang.com/api/v1/knowledge/claims/1034297MCP
get_claim(id=1034297)