20 citations · 25 across the 6 of their papers we have counts for
6 papers
Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models
Qianshan Wei, Jiaqi Li, Zihan You +9
Differential Privacy (DP) is a widely adopted technique, valued for its effectiveness in protecting the privacy of task-specific datasets, making it a critical tool for large langu…
From Superficial to Deep: Integrating External Knowledge for Follow-up Question Generation Using Knowledge Graph and LLM
Jianyu Liu, Yi Huang, Sheng Bi +2
In a conversational system, dynamically generating follow-up questions based on context can help users explore information and provide a better user experience. Humans are usually…
PRIMO: Progressive Induction for Multi-hop Open Rule Generation
Jianyu Liu, Sheng Bi, Guilin Qi
Open rule refer to the implication from premise atoms to hypothesis atoms, which captures various relations between instances in the real world. Injecting open rule knowledge into…
Can Large Language Models Understand DL-Lite Ontologies? An Empirical Study
Keyu Wang, Guilin Qi, Jiaqi Li +1
Large language models (LLMs) have shown significant achievements in solving a wide range of tasks. Recently, LLMs' capability to store, retrieve and infer with symbolic knowledge h…
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models
Jiaqi Li, Qianshan Wei, Chuanyi Zhang +5
Machine unlearning empowers individuals with the `right to be forgotten' by removing their private or sensitive information encoded in machine learning models. However, it remains…
The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions
Amin Ullah, Guilin Qi, Saddam Hussain +2
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living standards, facilitating the rapid expansion of urban areas while efficiently managing reso…