RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks

Zeyu Zhang, Jiamou Liu, Xianda Zheng, Yifei Wang, Pengqian Han, Yupan Wang, Kaiqi Zhao 0001, Zijian Zhang 0001. RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks. In Ying Ding 0001, Jie Tang 0001, Juan F. Sequeda, Lora Aroyo, Carlos Castillo 0001, Geert-Jan Houben, editors, Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023- 4 May 2023. pages 60-70, ACM, 2023. [doi]

Abstract

Abstract is missing.