Establishes sample complexity bounds for watermark proportion estimation under Gumbel-max, showing full observation is more efficient than pivotal reduction.
Optimal estimation of watermark proportions in hybrid ai-human texts
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Derives matched converse and achievability bounds that characterize optimal trade-offs among false-alarm probability, detection error probability, distortion, and information rate for multi-bit watermarking of stationary ergodic stochastic processes.
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Sample Complexities of Estimating Gumbel--Max Watermark Proportions with and without Reduction to Pivotal Statistics
Establishes sample complexity bounds for watermark proportion estimation under Gumbel-max, showing full observation is more efficient than pivotal reduction.
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Fundamental Trade-Offs in Multi-Bit Watermarking of Stochastic Processes
Derives matched converse and achievability bounds that characterize optimal trade-offs among false-alarm probability, detection error probability, distortion, and information rate for multi-bit watermarking of stationary ergodic stochastic processes.