Flip, Don't Shuffle: Watermarking LLMs at the Speed of Inference
A faster way to prove an AI wrote something, without slowing it down
Researchers created a new watermarking method for large language models that identifies AI-generated text while running 6000 times faster than existing techniques and adding less than 1% to generation speed. The method works by making a single random decision per word instead of searching through lists or running complex procedures, yet maintains the same ability to detect AI text with statistical certainty.
As AI-generated text becomes harder to distinguish from human writing, watermarks are a leading tool to prove authenticity—but existing methods slow down text generation noticeably. This technique is fast enough to deploy at scale without slowing down AI services, making it practical for real-world use in detecting plagiarism, academic cheating, and AI-generated misinformation.