GaussMark embeds a detectable watermark by adding per-generation Gaussian noise to one weight matrix and detecting gradient alignment with that noise.
Democratizing Neural Machine Translation with OPUS-MT
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abstract
This paper presents the OPUS ecosystem with a focus on the development of open machine translation models and tools, and their integration into end-user applications, development platforms and professional workflows. We discuss our on-going mission of increasing language coverage and translation quality, and also describe on-going work on the development of modular translation models and speed-optimized compact solutions for real-time translation on regular desktops and small devices.
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GaussMark: A Practical Approach for Structural Watermarking of Language Models
GaussMark embeds a detectable watermark by adding per-generation Gaussian noise to one weight matrix and detecting gradient alignment with that noise.