Verified65% confidenceFactExact time
The inherently stochastic sampling of diffusion models means that each generation result differs even given the same prompt.
3
Sources
65%
Confidence
Long-term
Relevance
7/17/2026
First Seen
Sources
Related Claims
Verified扩散模型在推理阶段从随机高斯噪声出发，经数十至数百步迭代去噪得到输出，即便固定随机种子，提示词的细微差异也会导致人脸特征、服装细节的显著偏移78% similarUnverifiedEach generation by a diffusion model is an independent random sampling process, causing the same character to potentially exhibit deviations in facial features, clothing details, and body proportions across different images.77% similarUnverifiedNon-determinism stems from the random sampling mechanism of model inference itself as well as vendors' continuous iteration on model versions.77% similarUnverifiedTo rule out randomness with statistical significance, a large number of repeated samples must be taken from the same model version within the same time window and compared as distributions against samples from another time window, rather than relying on single-sample comparisons.76% similarUnverifiedInstantiating multiple agents from the same base model is mathematically equivalent to performing correlated sampling of the same random variable, and the variance of the aggregated result will not shrink with increasing numbers the way independent sampling would.76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/540637API
curl https://kongchang.com/api/v1/knowledge/claims/540637MCP
get_claim(id=540637)