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Accelerating Large-Vocabulary Language Models by guanfelixcaptain is a document available to read on EtoBox.

The document presents FR-Spec, a frequency-ranked speculative sampling framework designed to enhance the efficiency of large-vocabulary language models (LLMs) by optimizing draft candidate selection through vocabulary space compression. By prioritizing high-frequency tokens, FR-Spec reduces computation overhead by 75% while maintaining output distribution equivalence, achieving an average speedup of 1.12× over existing methods like EAGLE-2. The framework is compatible with current speculative sampling techn

Author
guanfelixcaptain
Language
EN