134 citations · 212 across the 11 of their papers we have counts for
11 papers
The Shadow Self: Intrinsic Value Misalignment in Large Language Model Agents
Chen Chen, Kim Young Il, Yuan Yang +7
Large language model (LLM) agents with extended autonomy unlock new capabilities, but also introduce heightened challenges for LLM safety. In particular, an LLM agent may pursue ob…
Efficient Privacy-Preserving Retrieval Augmented Generation with Distance-Preserving Encryption
Huanyi Ye, Jiale Guo, Ziyao Liu +1
RAG has emerged as a key technique for enhancing response quality of LLMs without high computational cost. In traditional architectures, RAG services are provided by a single entit…
Attribution Techniques for Mitigating Hallucinated Information in RAG Systems: A Survey
Yuqing Zhao, Ziyao Liu, Yongsen Zheng +1
Large Language Models (LLMs)-based question answering (QA) systems play a critical role in modern AI, demonstrating strong performance across various tasks. However, LLM-generated…
FROC: A Unified Framework with Risk-Optimized Control for Machine Unlearning in LLMs
Si Qi Goh, Yongsen Zheng, Ziyao Liu +2
Machine unlearning (MU) seeks to eliminate the influence of specific training examples from deployed models. As large language models (LLMs) become widely used, managing risks aris…
Why Multi-Interest Fairness Matters: Hypergraph Contrastive Multi-Interest Learning for Fair Conversational Recommender System
Yongsen Zheng, Zongxuan Xie, Guohua Wang +3
Unfairness is a well-known challenge in Recommender Systems (RSs), often resulting in biased outcomes that disadvantage users or items based on attributes such as gender, race, age…
Deep Learning Approaches for Anti-Money Laundering on Mobile Transactions: Review, Framework, and Directions
Jiani Fan, Lwin Khin Shar, Ruichen Zhang +5
Money laundering is a financial crime that obscures the origin of illicit funds, necessitating the development and enforcement of anti-money laundering (AML) policies by government…
Efficient Federated Unlearning with Adaptive Differential Privacy Preservation
Yu Jiang, Xindi Tong, Ziyao Liu +3
Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL),…
Privacy-preserving Anomaly Detection in Cloud Manufacturing via Federated Transformer
Shiyao Ma, Jiangtian Nie, Jiawen Kang +5
With the rapid development of cloud manufacturing, industrial production with edge computing as the core architecture has been greatly developed. However, edge devices often suffer…
Efficient Dropout-resilient Aggregation for Privacy-preserving Machine Learning
Ziyao Liu, Jiale Guo, Kwok-Yan Lam +1
With the increasing adoption of data-hungry machine learning algorithms, personal data privacy has emerged as one of the key concerns that could hinder the success of digital trans…
MPC-enabled Privacy-Preserving Neural Network Training against Malicious Attack
Ziyao Liu, Ivan Tjuawinata, Chaoping Xing +1
The application of secure multiparty computation (MPC) in machine learning, especially privacy-preserving neural network training, has attracted tremendous attention from the resea…
A Survey on Applications of Game Theory in Blockchain
Ziyao Liu, Nguyen Cong Luong, Wenbo Wang +4
In the past decades, the blockchain technology has attracted tremendous attention from both academia and industry. The popularity of blockchain networks was originated from a crypt…