5 citations · 7 across the 11 of their papers we have counts for
11 papers
NOIR: Privacy-Preserving Generation of Code with Open-Source LLMs
Khoa Nguyen, Khiem Ton, NhatHai Phan +6
Although boosting software development performance, large language model (LLM)-powered code generation introduces intellectual property and data security risks rooted in the fact t…
-STEAL: LLM Stealing Attack with Local Differential Privacy
Kieu Dang, Phung Lai, NhatHai Phan +3
Large language models (LLMs) demonstrate remarkable capabilities across various tasks. However, their deployment introduces significant risks related to intellectual property. In t…
SoK: Are Watermarks in LLMs Ready for Deployment?
Kieu Dang, Phung Lai, NhatHai Phan +4
Large Language Models (LLMs) have transformed natural language processing, demonstrating impressive capabilities across diverse tasks. However, deploying these models introduces cr…
FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning
Phung Lai, Xiaopeng Jiang, Hai Phan +5
Federated Learning (FL) allows collaborative training among multiple devices without data sharing, thus enabling privacy-sensitive applications on mobile or Internet of Things (IoT…
Demo: SGCode: A Flexible Prompt-Optimizing System for Secure Generation of Code
Khiem Ton, Nhi Nguyen, Mahmoud Nazzal +6
This paper introduces SGCode, a flexible prompt-optimizing system to generate secure code with large language models (LLMs). SGCode integrates recent prompt-optimization approaches…
Fairness-Sensitive Policy-Gradient Reinforcement Learning for Reducing Bias in Robotic Assistance
Jie Zhu, Mengsha Hu, Xueyao Liang +3
Robots assist humans in various activities, from daily living public service (e.g., airports and restaurants), and to collaborative manufacturing. However, it is risky to assume th…
Zone-based Federated Learning for Mobile Sensing Data
Xiaopeng Jiang, Thinh On, NhatHai Phan +5
Mobile apps, such as mHealth and wellness applications, can benefit from deep learning (DL) models trained with mobile sensing data collected by smart phones or wearable devices. H…
Generation-Augmented Query Expansion For Code Retrieval
Dong Li, Yelong Shen, Ruoming Jin +3
Pre-trained language models have achieved promising success in code retrieval tasks, where a natural language documentation query is given to find the most relevant existing code s…
Towards Reliable Item Sampling for Recommendation Evaluation
Dong Li, Ruoming Jin, Zhenming Liu +3
Since Rendle and Krichene argued that commonly used sampling-based evaluation metrics are "inconsistent" with respect to the global metrics (even in expectation), there have been a…
Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning
Phung Lai, Han Hu, NhatHai Phan +3
In this paper, we show that the process of continually learning new tasks and memorizing previous tasks introduces unknown privacy risks and challenges to bound the privacy loss. B…
FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps
Xiaopeng Jiang, Han Hu, Vijaya Datta Mayyuri +6
This article presents the design, implementation, and evaluation of FLSys, a mobile-cloud federated learning (FL) system, which can be a key component for an open ecosystem of FL m…