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cs.LG2024
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction
Yinhan He, Zaiyi Zheng, Patrick Soga +3
In recent years, Graph Neural Networks (GNNs) have become successful in molecular property prediction tasks such as toxicity analysis. However, due to the black-box nature of GNNs,…
cs.LG2024★ 1 cited
A Benchmark for Fairness-Aware Graph Learning
Yushun Dong, Song Wang, Zhenyu Lei +4
Fairness-aware graph learning has gained increasing attention in recent years. Nevertheless, there lacks a comprehensive benchmark to evaluate and compare different fairness-aware…
cs.CL2024★ 2 cited
AI-native Memory: A Pathway from LLMs Towards AGI
Jingbo Shang, Zai Zheng, Jiale Wei +3
Large language models (LLMs) have demonstrated the world with the sparks of artificial general intelligence (AGI). One opinion, especially from some startups working on LLMs, argue…