{"list":"other","total":53,"rows":[{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"1609.02907","title":"Semi-Supervised Classification with Graph Convolutional Networks","created":"2016-09-09","cited_by_count":11361},{"id":"1710.10903","title":"Graph Attention Networks","created":"2017-10-30","cited_by_count":8923},{"id":"1706.02216","title":"Inductive Representation Learning on Large Graphs","created":"2017-06-07","cited_by_count":6320},{"id":"1903.02428","title":"Fast Graph Representation Learning with PyTorch Geometric","created":"2019-03-06","cited_by_count":2434},{"id":"1902.07153","title":"Simplifying Graph Convolutional Networks","created":"2019-02-19","cited_by_count":1477},{"id":"1810.05997","title":"Predict then Propagate: Graph Neural Networks meet Personalized PageRank","created":"2018-10-14","cited_by_count":993},{"id":"1805.07984","title":"Adversarial Attacks on Neural Networks for Graph Data","created":"2018-05-21","cited_by_count":397},{"id":"2208.11970","title":"Understanding Diffusion Models: A Unified Perspective","created":"2022-08-25","cited_by_count":340},{"id":"1806.02371","title":"Adversarial Attack on Graph Structured Data","created":"2018-06-06","cited_by_count":301},{"id":"1902.08412","title":"Adversarial Attacks on Graph Neural Networks via Meta Learning","created":"2019-02-22","cited_by_count":261},{"id":"2008.08692","title":"Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters","created":"2020-08-19","cited_by_count":250},{"id":"1906.04214","title":"Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective","created":"2019-06-10","cited_by_count":196},{"id":"1812.10528","title":"Adversarial Attack and Defense on Graph Data: A Survey","created":"2018-12-26","cited_by_count":167},{"id":"1803.00816","title":"NetGAN: Generating Graphs via Random Walks","created":"2018-03-02","cited_by_count":131},{"id":"2004.11648","title":"GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media","created":"2020-04-24","cited_by_count":109},{"id":"1407.5225","title":"The Rise of Social Bots","created":"2014-07-19","cited_by_count":96},{"id":"2002.12307","title":"Heterogeneous Graph Neural Networks for Malicious Account Detection","created":"2020-02-27","cited_by_count":96},{"id":"2005.06149","title":"DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses","created":"2020-05-13","cited_by_count":78},{"id":"1608.00375","title":"Hiding Individuals and Communities in a Social Network","created":"2016-08-01","cited_by_count":77},{"id":"2106.06663","title":"TDGIA:Effective Injection Attacks on Graph Neural Networks","created":"2021-06-12","cited_by_count":67},{"id":"1809.02797","title":"Fast Gradient Attack on Network Embedding","created":"2018-09-08","cited_by_count":65},{"id":"1911.09179","title":"Scalable and Generalizable Social Bot Detection through Data Selection","created":"2019-11-20","cited_by_count":59},{"id":"2106.13088","title":"TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark","created":"2021-06-24","cited_by_count":51},{"id":"1701.03017","title":"The paradigm-shift of social spambots: Evidence, theories, and tools for the arms race","created":"2017-01-11","cited_by_count":49},{"id":"2007.03604","title":"A Decade of Social Bot Detection","created":"2020-06-23","cited_by_count":48},{"id":"2108.13049","title":"Single Node Injection Attack against Graph Neural Networks","created":"2021-08-30","cited_by_count":45},{"id":"2206.04564","title":"TwiBot-22: Towards Graph-Based Twitter Bot Detection","created":"2022-06-09","cited_by_count":44},{"id":"2109.02927","title":"Heterogeneity-aware Twitter Bot Detection with Relational Graph Transformers","created":"2021-09-07","cited_by_count":41},{"id":"2106.13092","title":"BotRGCN: Twitter Bot Detection with Relational Graph Convolutional Networks","created":"2021-06-24","cited_by_count":39},{"id":"1802.04289","title":"Deep Neural Networks for Bot Detection","created":"2018-02-12","cited_by_count":37},{"id":"1509.04098","title":"Fame for sale: efficient detection of fake Twitter followers","created":"2015-09-14","cited_by_count":33},{"id":"2002.01336","title":"Twitter Bot Detection Using Bidirectional Long Short-term Memory Neural Networks and Word Embeddings","created":"2020-02-03","cited_by_count":25},{"id":"2106.13089","title":"SATAR: A Self-supervised Approach to Twitter Account Representation Learning and its Application in Bot Detection","created":"2021-06-24","cited_by_count":24},{"id":"2302.07363","title":"Attacking Fake News Detectors via Manipulating News Social Engagement","created":"2023-02-14","cited_by_count":23},{"id":"2004.04834","title":"Friend or Faux: Graph-Based Early Detection of Fake Accounts on Social Networks","created":"2020-04-09","cited_by_count":19},{"id":"2304.06280","title":"BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts","created":"2023-04-13","cited_by_count":18},{"id":"2404.13595","title":"Unsupervised Social Bot Detection via Structural Information Theory","created":"2024-04-21","cited_by_count":18},{"id":"2206.06757","title":"RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture Search","created":"2022-06-14","cited_by_count":17},{"id":"1602.00110","title":"DNA-inspired online behavioral modeling and its application to spambot detection","created":"2016-01-30","cited_by_count":16},{"id":"2301.01123","title":"MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmark","created":"2023-01-03","cited_by_count":16},{"id":"2405.11225","title":"SeBot: Structural Entropy Guided Multi-View Contrastive Learning for Social Bot Detection","created":"2024-05-18","cited_by_count":16},{"id":"2208.08320","title":"BIC: Twitter Bot Detection with Text-Graph Interaction and Semantic Consistency","created":"2022-08-17","cited_by_count":14},{"id":"2304.12000","title":"Hierarchical State Abstraction Based on Structural Information Principles","created":"2023-04-24","cited_by_count":14},{"id":"2303.07113","title":"FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection","created":"2023-03-10","cited_by_count":12},{"id":"2404.15744","title":"A General Black-box Adversarial Attack on Graph-based Fake News Detectors","created":"2024-04-24","cited_by_count":11},{"id":"2404.15070","title":"BotDGT: Dynamicity-aware Social Bot Detection with Dynamic Graph Transformers","created":"2024-04-23","cited_by_count":10},{"id":"1904.05132","title":"Better Safe Than Sorry: An Adversarial Approach to Improve Social Bot Detection","created":"2019-04-10","cited_by_count":8},{"id":"2304.08239","title":"RF-GNN: Random Forest Boosted Graph Neural Network for Social Bot Detection","created":"2023-04-14","cited_by_count":5},{"id":"2310.07159","title":"My Brother Helps Me: Node Injection Based Adversarial Attack on Social Bot Detection","created":"2023-10-11","cited_by_count":5},{"id":"2011.03574","title":"Single-Node Attacks for Fooling Graph Neural Networks","created":"2020-11-06","cited_by_count":4},{"id":"2506.00989","title":"Boosting Bot Detection via Heterophily-Aware Representation Learning and Prototype-Guided Cluster Discovery","created":"2025-06-01","cited_by_count":4},{"id":"2110.10655","title":"Socialbots on Fire: Modeling Adversarial Behaviors of Socialbots via Multi-Agent Hierarchical Reinforcement Learning","created":"2021-10-20","cited_by_count":3}],"next_cursor":null}