Unverified50% confidenceBenchmarkExact time
Under the same average activated parameter budget, LRCC improves average downstream task accuracy by 7.6 percentage points on Llama-2-7B compared to static methods.
1
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50%
Confidence
Long-term
Relevance
10/8/2026
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Related Claims
UnverifiedIn actual testing, llama.cpp combined with llama-swap can achieve 75–80 tokens per second, and the author considers it faster and easier to use than Ollama.59% similarUnverified对于Turbo类模型，专用采样器（如LCM Sampler）通常优于通用采样器（如DPM++），CFG引导强度通常在5至12之间寻找最佳平衡点58% similarUnverifiedLRA的响应延迟通常低于10ms，比传统偏心旋转质量（ERM）马达更精确56% similar
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