Jiaqi Zhu

LLM-Empowered Few-Shot Node Classification on Incomplete Graphs with Real Node Degrees

2024

Graphs constructed from real-world scenarios are often incomplete due to privacy restrictions or resource limitations, posing significant challenges for node classification, especially when labeled data are scarce. In many scenarios of incomplete graphs, the real …

Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix

2025

Large language models (LLMs) typically require fine-tuning for domain-specific tasks, and LoRA offers a computationally efficient approach by training low-rank adapters. LoRA is also communication-efficient for federated LLMs when multiple users collaboratively fine-tune a global …