Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks

1 code implementation • NeurIPS 2023 • Jiarong Xu, Renhong Huang, Xin Jiang, Yuxuan Cao, Carl Yang, Chunping Wang, Yang Yang

The proposed pre-training pipeline is called the data-active graph pre-training (APT) framework, and is composed of a graph selector and a pre-training model.

Cross-Lingual Knowledge Editing in Large Language Models

2 code implementations • 16 Sep 2023 • Jiaan Wang, Yunlong Liang, Zengkui Sun, Yuxuan Cao, Jiarong Xu

With the recent advancements in large language models (LLMs), knowledge editing has been shown as a promising technique to adapt LLMs to new knowledge without retraining from scratch.

knowledge editing

When to Pre-Train Graph Neural Networks? From Data Generation Perspective!

1 code implementation • 29 Mar 2023 • Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei Chen, Yang Yang

All convex combinations of graphon bases give rise to a generator space, from which graphs generated form the solution space for those downstream data that can benefit from pre-training.