Verified75% confidenceFactExact time
Speculative decoding is a lossless acceleration technique that does not alter the model's output distribution; it uses a draft model with far fewer parameters than the target model to generate candidate tokens, which the target model then verifies in parallel.
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75%
Confidence
Long-term
Relevance
9/1/2026
First Seen
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Related Claims
UnverifiedSpeculative decoding generates drafts with a small model and verifies them in batch with a large model; mathematically it guarantees output fully consistent with the large model through rejection sampling, making it lossless acceleration80% similarVerifiedSpeculative Decoding reduces computation by using a small model to predict the output tokens of a large model77% similarUnverified分类模型的推理是非自回归的，仅需一次前向传播即可完成所有位置预测，计算效率显著高于生成模型77% similarVerifiedSpeculative 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.77% similarUnverified该模型的架构设计目标是让每个token的解码速度只取决于激活参数而非总参数77% similar
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