Author

John Le

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Open access Aug 2026

A cross-graph tuning-free GNN prompting framework.

GNN prompting aims to adapt models across tasks and graphs without requiring extensive retraining. However, most existing graph prompt methods still require task-specific parameter updates and face the issue of generalizing across graphs, limiting their performance and undermining the core promise of prompting. In this...

Yaqi Chen, Shi-Xun Huang, Lei Wang et al. · Neural Networks · 0 citations

Review Open access Jun 2026

Augmenting Large Language Models with External Data Sources: A Systematic Review of Methodologies, Performance Metrics, and Information Fidelity

This review focuses specifically on Retrieval-Augmented Generation and fine-tuning, identifying them as the two dominant paradigms for integrating external knowledge: RAG for retrieval-based context injection and fine-tuning for parametric knowledge adaptation.

Soham Mukherjee, John Le, Chau Nguyen · Knowledge · 0 citations