3 papers
cs.CL2025
KSOD: Knowledge Supplement for LLMs On Demand
Haoran Li, Junfeng Hu
Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks, yet still produce errors in domain-specific tasks. To further improve their performance, we…
cs.LG2024
Prompt-Based Spatio-Temporal Graph Transfer Learning
Junfeng Hu, Xu Liu, Zhencheng Fan +4
Spatio-temporal graph neural networks have proven efficacy in capturing complex dependencies for urban computing tasks such as forecasting and kriging. Yet, their performance is co…
cs.LG2024
Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning
Junfeng Hu, Xu Liu, Zhencheng Fan +2
Spatio-temporal graph learning is a fundamental problem in modern urban systems. Existing approaches tackle different tasks independently, tailoring their models to unique task cha…