A power-calibrated statistical framework gives closed-form links from KGW watermark parameters (γ, δ) to detection power and KL distortion, enabling principled Pareto-optimal selection.
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Nomic AI produced and open-sourced a reproducible 8192-context English text embedder that exceeds OpenAI Ada-002 and text-embedding-3-small performance on MTEB short-context and LoCo long-context benchmarks.
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Beyond Heuristic Tuning: Power-Calibrated LLM Watermarking
A power-calibrated statistical framework gives closed-form links from KGW watermark parameters (γ, δ) to detection power and KL distortion, enabling principled Pareto-optimal selection.
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Nomic Embed: Training a Reproducible Long Context Text Embedder
Nomic AI produced and open-sourced a reproducible 8192-context English text embedder that exceeds OpenAI Ada-002 and text-embedding-3-small performance on MTEB short-context and LoCo long-context benchmarks.