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New framework RoSeMary embeds secure watermarks in LLM-generated code

By PulseAugur Editorial · [1 sources] ·

Researchers have developed RoSeMary, a novel framework for watermarking code generated by large language models. This system uses a combination of machine learning and cryptography to embed watermarks that can be securely verified without revealing the underlying signature, thus protecting intellectual property and preventing misuse. RoSeMary leverages a pre-trained CodeT5 model to ensure watermarked code maintains its functionality while enhancing detectability and robustness against various attacks. AI

IMPACT Enhances security and intellectual property protection for LLM-generated code, potentially impacting software development workflows.

RANK_REASON The item is a research paper detailing a new method for watermarking LLM-generated code. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework RoSeMary embeds secure watermarks in LLM-generated code

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The item is a research paper detailing a new method for watermarking LLM-generated code. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ruisi Zhang, Neusha Javidnia, Nojan Sheybani, Farinaz Koushanfar ·

    Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign

    arXiv:2502.02068v3 Announce Type: replace-cross Abstract: This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid intellectual property rights violations and inappropriate misuse in software develo…

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