A binomial multibit watermarking scheme encodes every payload bit at each LLM token with dynamic redirection, outperforming baselines in accuracy and robustness for large payloads.
Advancing beyond identification: Multi- bit watermark for large language models
4 Pith papers cite this work. Polarity classification is still indexing.
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Characterizes the exact capacity of multi-bit covert LLM watermarking via Gelfand-Pinsker and channel synthesis, then gives a polar-code algorithm achieving 0.375 bits/token at under 10% BER with negligible perplexity impact.
The thesis presents a kernel method for multiaccuracy across overlooked subpopulations, information-theoretic optimal watermarking for LLMs, and a simulator showing LLM agents outperforming humans in supply chains while creating tail risks.
Response times modeled as drift-diffusion processes enable consistent estimation of population-average preferences from heterogeneous anonymous binary choices.
citing papers explorer
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Every Bit, Everywhere, All at Once: A Binomial Multibit LLM Watermark
A binomial multibit watermarking scheme encodes every payload bit at each LLM token with dynamic redirection, outperforming baselines in accuracy and robustness for large payloads.
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Covert Multi-bit LLM Watermarking: An Information Theory and Coding Approach
Characterizes the exact capacity of multi-bit covert LLM watermarking via Gelfand-Pinsker and channel synthesis, then gives a polar-code algorithm achieving 0.375 bits/token at under 10% BER with negligible perplexity impact.
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Trustworthy AI: Ensuring Reliability and Accountability from Models to Agents
The thesis presents a kernel method for multiaccuracy across overlooked subpopulations, information-theoretic optimal watermarking for LLMs, and a simulator showing LLM agents outperforming humans in supply chains while creating tail risks.
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Response Time Enhances Alignment with Heterogeneous Preferences
Response times modeled as drift-diffusion processes enable consistent estimation of population-average preferences from heterogeneous anonymous binary choices.