Longlong Zhang — accepted AI-conference papers

2026

BotVA: Combating Social Bots via Variational Feature Augmentation and Adversarial Graph Learning

Longlong Zhang, Xi Wang, Hongyi Nie, Zeqing Zhang, Huixiang Zhang, Hongping Wang +1

IJCAI 2026

Social bots threaten online platforms by spreading disinformation and manipulating public discourse. Graph neural networks have emerged as effective tools for bot detection by modeling user interactions, yet two fundamental challenges limit their practical deployment: severe class imbalance where bo

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2026

RABot: Reinforcement-Guided Graph Augmentation for Imbalanced and Noisy Social Bot Detection

Longlong Zhang, Xi Wang, Haotong Du, Yangyi Xu, Zhuo Liu, Yang Liu

AAAI 2026technical

Social bot detection is pivotal for safeguarding the integrity of online information ecosystems. Although recent graph neural network (GNN) solutions achieve strong results, they remain hindered by two practical challenges: (i) severe class imbalance arising from the high cost of generating bots, an

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