Unverified50% confidenceFactExact time
This version supports model outputs accompanied by probability distributions across options and confidence metadata
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/16/2026
First Seen
Valid until: 12/15/2026
Sources
Related Entities
Related Claims
UnverifiedMainstream generative models such as diffusion models and flow matching models are essentially probabilistic generators that produce new samples by sampling from data distributions.71% similarUnverified生成式模型建模联合概率 P(x,y) 或数据分布 P(x)，而判别式模型直接建模条件概率 P(y|x)；生成模型在小样本时更具优势，判别模型在大数据量时通常表现更好71% similarUnverifiedA model may produce a seemingly credible result based on incomplete data.69% similarUnverifiedLarge language models are fundamentally performing probabilistic predictions of the next most likely token in a sequence.68% similarUnverifiedA prompt is essentially the 'condition' for the model; the more precise the condition, the more concentrated the model's probability distribution becomes on the user's desired output, rather than being spread across all directions.68% similar
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