AI Watermarking Limits: Low-Entropy Outputs Missed, But Social Benefits Outweigh Costs
RyanGreenblatt · x · 2026-08-12
Continuing the discussion on LLM watermarking mechanisms, researcher Ryan Greenblatt pointed out that because low-entropy outputs (such as very short texts or highly deterministic responses) cannot be effectively watermarked, minor edits to text will likely bypass watermark tracing.
Despite these technical limitations, he guesses that the overall social benefits of implementing watermarking outweigh the costs. He specifically mentioned existing AI text detection tools like Pangram as a comparison, suggesting that such mechanisms are generally positive for the ecosystem, though he remains not super confident about this conclusion.
Related event: Researcher Analyzes LLM Watermarks: Low-Entropy Outputs Hard to Tag(3 posts)→
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