Unverified50% confidenceFactExact time
The time cost for the main model to verify N tokens in parallel is almost the same as verifying 1 token, and the overall throughput improves linearly with the draft model's hit rate.
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50%
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Long-term
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9/29/2026
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Related Claims
VerifiedSpeculative Decoding uses a small, fast draft model to predict multiple tokens in advance, which are then verified in parallel all at once by the large model.76% similarUnverified一致性正则化的基本假设是对同一输入样本施加不同扰动时模型输出应保持一致75% similarUnverified重复运行以计算通过率比依赖单次结果更能反映模型的真实表现73% similarUnverifiedTraditional autoregressive methods require N forward passes to generate N tokens, whereas speculative decoding consolidates multiple calls into one through batch verification.71% similarUnverifiedSpeculative decoding improves generation throughput while guaranteeing that the output is completely identical to that of the original model.69% similar
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