5 citations · 5 across the 5 of their papers we have counts for
5 papers
Thermo-FL: Thermal-Aware Robust Federated Fine-Tuning of Large Language Models for Edge AI
Shiva Shrestha, Kazi Shaharair Sharif, Zongxing Xie +3
Federated fine-tuning enables large language models to adapt on edge devices without centralizing private data, but practical deployments must address hardware instability and adve…
Masking Is Not Enough: Generative Restoration for Multimodal De-Identification in Medical AI
Shiva Shrestha, Zongxing Xie, Chen Zhao +3
Medical image-text data can expose protected health information (PHI) through both visible image content as well as accompanying text, creating a barrier to privacy-preserving medi…
COMIC: Reference-Aware Safety Gating for Multimodal Large Language Models
Md Abdullahil Oaphy, Anhao Xiang, Zongxing Xie +3
Multimodal large language models (MLLMs) are increasingly used to interact with screenshots, scanned documents, diagrams, and other visually grounded inputs. This shift introduces…
How Privacy-Savvy Are Large Language Models? A Case Study on Compliance and Privacy Technical Review
Yang Liu, Xichou Zhu, Zhou Shen +13
The recent advances in large language models (LLMs) have significantly expanded their applications across various fields such as language generation, summarization, and complex que…
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey
Chengyuan Deng, Yiqun Duan, Xin Jin +15
Large Language Models (LLMs) have achieved unparalleled success across diverse language modeling tasks in recent years. However, this progress has also intensified ethical concerns…