13 citations · 27 across the 13 of their papers we have counts for
14 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…
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…
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…
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…
Watermarking Large Language Models and the Generated Content: Opportunities and Challenges
Ruisi Zhang, Farinaz Koushanfar
The widely adopted and powerful generative large language models (LLMs) have raised concerns about intellectual property rights violations and the spread of machine-generated misin…
Automated Physical Design Watermarking Leveraging Graph Neural Networks
Ruisi Zhang, Rachel Selina Rajarathnam, David Z. Pan +1
This paper presents AutoMarks, an automated and transferable watermarking framework that leverages graph neural networks to reduce the watermark search overheads during the placeme…
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…
EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models
Ruisi Zhang, Farinaz Koushanfar
This paper introduces EmMark,a novel watermarking framework for protecting the intellectual property (IP) of embedded large language models deployed on resource-constrained edge de…
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Mingjia Huo, Sai Ashish Somayajula, Youwei Liang +3
Large language models generate high-quality responses with potential misinformation, underscoring the need for regulation by distinguishing AI-generated and human-written texts. Wa…
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks
Nasimeh Heydaribeni, Xinrui Zhan, Ruisi Zhang +2
Scalable addressing of high dimensional constrained combinatorial optimization problems is a challenge that arises in several science and engineering disciplines. Recent work intro…
REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models
Ruisi Zhang, Shehzeen Samarah Hussain, Paarth Neekhara +1
We present REMARK-LLM, a novel efficient, and robust watermarking framework designed for texts generated by large language models (LLMs). Synthesizing human-like content using LLMs…
SureFED: Robust Federated Learning via Uncertainty-Aware Inward and Outward Inspection
Nasimeh Heydaribeni, Ruisi Zhang, Tara Javidi +2
In this work, we introduce SureFED, a novel framework for byzantine robust federated learning. Unlike many existing defense methods that rely on statistically robust quantities, ma…
Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers
Ruisi Zhang, Seira Hidano, Farinaz Koushanfar
Text classification has become widely used in various natural language processing applications like sentiment analysis. Current applications often use large transformer-based langu…