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Watermarkable Multi-Draft Speculative Sampling via Poisson Processes

Research Efficiency & Systems

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TL;DR - This paper introduces a Poisson-process-based multi-draft speculative sampling algorithm that supports unbiased watermarking without reducing speculative acceptance. It advances the trade-off between efficient LLM inference and reliable output provenance.

  • Uses an exact list-coupling-without-communication scheme to enable multi-draft speculative sampling.
  • Provides drafter invariance, benefiting both sampling efficiency and watermark robustness.
  • Preserves watermark strength without sacrificing speculative acceptance.
  • Experiments report strong performance across both sampling efficiency and watermarking.

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Watermarkable Multi-Draft Speculative Sampling via Poisson Processes

arXiv cs.CR Yanxiao Liu, Sicheng Wan, Zhan Gao, Deniz GĂĽndĂĽz 2026-09-18 arXiv:2609.21858
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Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-26 14:14:56.279415 UTC

TL;DR - This paper introduces a Poisson-process-based multi-draft speculative sampling algorithm that supports unbiased watermarking without reducing speculative acceptance. It advances the trade-off between efficient LLM inference and reliable output provenance.

  • Uses an exact list-coupling-without-communication scheme to enable multi-draft speculative sampling.
  • Provides drafter invariance, benefiting both sampling efficiency and watermark robustness.
  • Preserves watermark strength without sacrificing speculative acceptance.
  • Experiments report strong performance across both sampling efficiency and watermarking.
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