Unverified50% confidenceBenchmarkExact time
On two model families and three types of reasoning and structured generation workloads, NgramRL can commit 3.60–7.77 tokens per target-model forward pass in the hot-cache setting.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/26/2026
First Seen
Valid until: 1/24/2027
Sources
Related Entities
Related Claims
UnverifiedToken Plans with shared quotas across multiple models involve model conversion rate issues, where the billed tokens consumed per call for different models may not equal the actual number of text tokens processed.68% similarUnverifiedThe method proceeds in three steps: repeatedly sampling a single prompt at high temperature to generate multiple completions, applying PCA dimensionality reduction to the hidden activations of the completions, and automatically assigning semantic labels to the positive and negative poles of each principal axis—all without updating model parameters.65% similarUnverified大模型推理的自回归生成需要逐Token串行输出，生成N个Token需要N次前向传播65% similarUnverifiedLarge models are billed by the number of input plus output Tokens for each inference.63% similarUnverifiedDraft models typically generate 3 to 8 candidate tokens at a time.62% similar
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