Defines Decision Potential Surface (DPS) whose zero isohypse equals an LLM decision boundary and supplies a K-sample approximation algorithm with derived upper bounds on absolute, expected, and concentration errors.
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A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.
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Decision Potential Surface: A Theoretical and Practical Approximation of Large Language Model Decision Boundary
Defines Decision Potential Surface (DPS) whose zero isohypse equals an LLM decision boundary and supplies a K-sample approximation algorithm with derived upper bounds on absolute, expected, and concentration errors.
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Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends
A survey of LLM copyright protection that unifies text watermarking, model watermarking, and model fingerprinting while presenting new coverage of fingerprint transfer and removal.