AutoMark: Enabling Autoresearch to Discover Better LLM Watermarks
AutoMark uses frontier-model agents to autonomously discover distortion-free LLM watermarks that beat prior schemes.
AutoMark defines reliability criteria, statistical tests, and a suite ranking LLM watermarks by detectability, quality, and robustness so agents can search for new distortion-free schemes. Using GPT-6 Astra, Opus 5, and Gemini-3.8 Flash, the authors report more than 50 schemes, including several that outperform prior work on all three dimensions. A manual study decomposes the schemes and identifies new ideas, such as aligning watermark scores with a random per-request direction. Code is released at eth-sri/automark.
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