7 papers
SWaRL: Safeguard Code Watermarking via Reinforcement Learning
Neusha Javidnia, Ruisi Zhang, Ashish Kundu +1
We present SWaRL, a robust and fidelity-preserving watermarking framework designed to protect the intellectual property of code LLMs by embedding unique and verifiable signatures i…
AttestLLM: Efficient Attestation Framework for Billion-scale On-device LLMs
Ruisi Zhang, Yifei Zhao, Neusha Javidnia +2
As on-device LLMs(e.g., Apple on-device Intelligence) are widely adopted to reduce network dependency, improve privacy, and enhance responsiveness, verifying the legitimacy of mode…
Optimizing Privacy-Preserving Primitives to Support LLM-Scale Applications
Yaman Jandali, Ruisi Zhang, Nojan Sheybani +1
Privacy-preserving technologies have introduced a paradigm shift that allows for realizable secure computing in real-world systems. The significant barrier to the practical adoptio…
ICMarks: A Robust Watermarking Framework for Integrated Circuit Physical Design IP Protection
Ruisi Zhang, Rachel Selina Rajarathnam, David Z. Pan +1
Physical design watermarking on contemporary integrated circuit (IC) layout encodes signatures without considering the dense connections and design constraints, which could lead to…
Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign
Ruisi Zhang, Neusha Javidnia, Nojan Sheybani +1
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 a…
SimpleFSDP: Simpler Fully Sharded Data Parallel with torch.compile
Ruisi Zhang, Tianyu Liu, Will Feng +4
Distributed training of large models consumes enormous computation resources and requires substantial engineering efforts to compose various training techniques. This paper present…