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A fixed span can recover most of the benefits of movable low-rank factors in LLM adaptation, achieving superior performance with drastically fewer trainable parameters.
TailSieve achieves up to 2.59x speedup in LLM rollouts by intelligently routing long-tail requests, transforming how we handle high-concurrency decoding.
