Waterfall: A Novel Framework for Robust and Scalable Text Watermarking and Provenance for Large Language Models
WATERFALL is a novel, training-free framework for robust and scalable text watermarking that leverages the power of large language models (LLMs) to protect intellectual property (IP) in various text formats, including articles and code, against plagiarism and unauthorized LLM training.
SynthID-Text: A Scalable Watermarking Scheme for Identifying Large Language Model-Generated Text
SynthID-Text is a production-ready watermarking technique for identifying text generated by large language models (LLMs) that maintains text quality, offers high detection accuracy, and integrates seamlessly with existing LLM deployment practices.
DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text
DeepTextMark introduces a deep learning-driven text watermarking approach for identifying text generated by Large Language Models, emphasizing blind, robust, reliable, automatic, and imperceptible characteristics.
DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text
DeepTextMark introduces a deep learning-driven text watermarking methodology for identifying large language model generated text.
DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text
DeepTextMark introduces a deep learning-driven text watermarking methodology for identifying large language model generated text, emphasizing blindness, robustness, imperceptibility, and reliability in text source detection.
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