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This work develops a novel multi-draft speculative sampling algorithm based on Poisson processes that maintains both watermark strength and sampling efficiency, and is the first multi-draft, drafter-invariant speculative sampling scheme that maintains both watermark strength and sampling efficiency.
Best-of-$n$ (BoN) sampling is a simple yet effective inference-time alignment method, but hard maximization provides only coarse control over the trade-off between reward and distribution shift. Soft Best-of-$n$ (Verdun et al. 2025) provides smoother control and converges to the optimal distribution associated with KL-...
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