Unverified50% confidenceFactExact time
The residual distribution is defined as: for tokens where the target model probability p(x) is greater than the draft model probability q(x), the residual probability is proportional to max(0, p(x) - q(x)).
1
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50%
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Long-term
Relevance
9/11/2026
First Seen
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UnverifiedThe verification process in traditional speculative decoding accepts draft-proposed tokens with probability min(1, p(x)/q(x)), and upon rejection resamples from the corrected distribution norm(max(0, p(x)-q(x))), which can be proven to produce a token distribution identical to directly sampling from the target model (lossless).72% similarUnverifiedAssuming the data follows a Gaussian distribution, maximizing the likelihood is equivalent to minimizing the mean squared error.69% similarUnverifiedWhen large numbers of users call the same underlying model with similar prompts, convergence of outputs is almost a mathematical inevitability due to the consistent underlying weights and probability distributions.66% similarUnverifiedLLM生成阶段对词汇表（通常包含32,000至128,000个token）计算Softmax概率分布，形成总和为1的概率向量65% similarUnverifiedA higher temperature value makes the model's output probability distribution smoother and increases randomness; Top-p sampling draws only from the smallest set of tokens whose cumulative probability reaches the threshold.65% similar
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