zwhe99/X-SIR
[ACL 2024] Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models
This project helps evaluate how well watermarks in text generated by Large Language Models (LLMs) persist, especially after the text has been translated into different languages. It takes text output from LLMs (either watermarked or not) and measures the detectability of the watermark, even after the text has been paraphrased or translated. This tool is for researchers and developers working on LLM watermarking techniques and their resilience.
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Use this if you need to assess the robustness of text watermarks embedded in LLM-generated content against common adversarial transformations like translation and paraphrasing.
Not ideal if you are a casual user looking for a simple tool to watermark your documents or detect AI-generated content without deep technical analysis.
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Python
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Last pushed
Jun 04, 2024
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