Text watermarks for large language models (LLMs) have been commonly used to identify the origins of machine-generated content, which is promising for assessing liability when combating deepfake or harmful content.

Despite the success of DPM in practice, the mechanism behind it remains to be explored.

We adopt a multi-armed bandit framework for this process, enhancing prompt selection based on the returns from online trajectories.