Flip, Don't Shuffle: Watermarking LLMs at the Speed of Inference
Stateless Bernoulli Watermarking (SBW) is introduced, a new statistical watermark for Large Language Models that determines green list membership through independent per-token Bernoulli trials, reducing membership complexity to $O(1)$ and enabling single-kernel execution with zero intermediate allocations.