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cs.LG2025
Towards Graph Foundation Models: A Transferability Perspective
Yuxiang Wang, Wenqi Fan, Suhang Wang +1
In recent years, Graph Foundation Models (GFMs) have gained significant attention for their potential to generalize across diverse graph domains and tasks. Some works focus on Doma…
cs.LG2025
Graph-based Molecular In-context Learning Grounded on Morgan Fingerprints
Ali Al-Lawati, Jason Lucas, Zhiwei Zhang +2
In-context learning (ICL) effectively conditions large language models (LLMs) for molecular tasks, such as property prediction and molecule captioning, by embedding carefully selec…
cs.LG2024
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark
Xiaowei Qian, Zhimeng Guo, Jialiang Li +4
Fair graph learning plays a pivotal role in numerous practical applications. Recently, many fair graph learning methods have been proposed; however, their evaluation often relies o…