{"total":78,"rows":[{"id":"2303.13047","title":"Towards Better Dynamic Graph Learning: New Architecture and Unified Library","created":"2023-03-23","cited_by_count":157,"area":null},{"id":"2302.11636","title":"Do We Really Need Complicated Model Architectures For Temporal Networks?","created":"2023-02-22","cited_by_count":143,"area":null},{"id":"2203.14883","title":"TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs","created":"2022-03-28","cited_by_count":61,"area":null},{"id":"2302.01018","title":"Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities","created":"2023-02-02","cited_by_count":61,"area":null},{"id":"2209.15059","title":"Provably expressive temporal graph networks","created":"2022-09-29","cited_by_count":56,"area":null},{"id":"2209.01084","title":"Neighborhood-aware Scalable Temporal Network Representation Learning","created":"2022-09-02","cited_by_count":54,"area":null},{"id":"2405.00476","title":"A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges","created":"2024-05-01","cited_by_count":30,"area":null},{"id":"2404.18211","title":"A survey of dynamic graph neural networks","created":"2024-04-28","cited_by_count":24,"area":null},{"id":"2406.07926","title":"Efficient Neural Common Neighbor for Temporal Graph Link Prediction","created":"2024-06-12","cited_by_count":18,"area":null},{"id":"2302.06057","title":"TIGER: Temporal Interaction Graph Embedding with Restarts","created":"2023-02-13","cited_by_count":17,"area":null},{"id":"2205.13084","title":"BRIGHT -- Graph Neural Networks in Real-Time Fraud Detection","created":"2022-05-25","cited_by_count":15,"area":null},{"id":"2304.05729","title":"Dynamic Graph Representation Learning with Neural Networks: A Survey","created":"2023-04-12","cited_by_count":15,"area":null},{"id":"2502.02975","title":"TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics","created":"2025-02-05","cited_by_count":15,"area":null},{"id":"2203.10480","title":"Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Survey","created":"2022-03-20","cited_by_count":14,"area":null},{"id":"2305.08273","title":"Decoupled Graph Neural Networks for Large Dynamic Graphs","created":"2023-05-14","cited_by_count":14,"area":null},{"id":"2305.13854","title":"The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey","created":"2023-05-23","cited_by_count":14,"area":null},{"id":"2402.11933","title":"SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning","created":"2024-02-19","cited_by_count":14,"area":null},{"id":"2408.04713","title":"DyGMamba: Efficiently Modeling Long-Term Temporal Dependency on Continuous-Time Dynamic Graphs with State Space Models","created":"2024-08-08","cited_by_count":14,"area":null},{"id":"2211.08568","title":"Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs","created":"2022-11-15","cited_by_count":13,"area":null},{"id":"2303.15015","title":"Towards Open Temporal Graph Neural Networks","created":"2023-03-27","cited_by_count":13,"area":null},{"id":"2203.05095","title":"Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA","created":"2022-03-10","cited_by_count":12,"area":null},{"id":"2307.07649","title":"DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training","created":"2023-07-14","cited_by_count":12,"area":null},{"id":"2402.15113","title":"MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline","created":"2024-02-23","cited_by_count":12,"area":null},{"id":"2311.18526","title":"HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers","created":"2023-11-30","cited_by_count":10,"area":null},{"id":"2112.09845","title":"Time-Aware Neighbor Sampling for Temporal Graph Networks","created":"2021-12-18","cited_by_count":9,"area":null},{"id":"2308.10779","title":"Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs","created":"2023-08-21","cited_by_count":9,"area":null},{"id":"2412.03864","title":"Training MLPs on Graphs without Supervision","created":"2024-12-05","cited_by_count":8,"area":null},{"id":"2207.03408","title":"Representation Learning in Continuous-Time Dynamic Signed Networks","created":"2022-07-07","cited_by_count":6,"area":null},{"id":"2312.02473","title":"NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams","created":"2023-12-05","cited_by_count":6,"area":null},{"id":"2407.16959","title":"Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding","created":"2024-07-24","cited_by_count":6,"area":null},{"id":"2412.16435","title":"THeGCN: Temporal Heterophilic Graph Convolutional Network","created":"2024-12-21","cited_by_count":6,"area":null},{"id":"2502.21185","title":"A Survey of Link Prediction in Temporal Networks","created":"2025-02-28","cited_by_count":6,"area":null},{"id":"2503.14411","title":"Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models","created":"2025-03-18","cited_by_count":6,"area":null},{"id":"2204.10614","title":"Modelling graph dynamics in fraud detection with \"Attention\"","created":"2022-04-22","cited_by_count":5,"area":null},{"id":"2208.06794","title":"DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction","created":"2022-08-14","cited_by_count":5,"area":null},{"id":"2302.11091","title":"GTRL: An Entity Group-Aware Temporal Knowledge Graph Representation Learning Method","created":"2023-02-22","cited_by_count":5,"area":null},{"id":"2409.05477","title":"Retrofitting Temporal Graph Neural Networks with Transformer","created":"2024-09-09","cited_by_count":5,"area":null},{"id":"2412.07273","title":"Temporal-Aware Evaluation and Learning for Temporal Graph Neural Networks","created":"2024-12-10","cited_by_count":5,"area":null},{"id":"2506.00431","title":"TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformer","created":"2025-05-31","cited_by_count":5,"area":null},{"id":"2205.15924","title":"Continuous Temporal Graph Networks for Event-Based Graph Data","created":"2022-05-31","cited_by_count":4,"area":null},{"id":"2309.02012","title":"iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation","created":"2023-09-05","cited_by_count":4,"area":null},{"id":"2407.19183","title":"Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networks","created":"2024-07-27","cited_by_count":4,"area":null},{"id":"2506.24018","title":"Bridging Theory and Practice in Link Representation with Graph Neural Networks","created":"2025-06-30","cited_by_count":4,"area":null},{"id":"2405.06975","title":"Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks","created":"2024-05-11","cited_by_count":3,"area":null},{"id":"2502.16431","title":"UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs","created":"2025-02-23","cited_by_count":3,"area":null},{"id":"2601.22454","title":"Temporal Graph Pattern Machine","created":"2026-01-30","cited_by_count":3,"area":null},{"id":"2108.08754","title":"Temporal Graph Network Embedding with Causal Anonymous Walks Representations","created":"2021-08-19","cited_by_count":2,"area":null},{"id":"2110.04559","title":"Graph Neural Networks in Real-Time Fraud Detection with Lambda Architecture","created":"2021-10-09","cited_by_count":2,"area":null},{"id":"2210.01171","title":"TPGNN: Learning High-order Information in Dynamic Graphs via Temporal Propagation","created":"2022-10-03","cited_by_count":2,"area":null},{"id":"2402.01964","title":"Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling","created":"2024-02-03","cited_by_count":2,"area":null},{"id":"2402.07199","title":"Link-aware link prediction over temporal graph by pattern recognition","created":"2024-02-11","cited_by_count":2,"area":null},{"id":"2405.05985","title":"TrafficGPT: Towards Multi-Scale Traffic Analysis and Generation with Spatial-Temporal Agent Framework","created":"2024-05-08","cited_by_count":2,"area":null},{"id":"2405.08013","title":"CTRL: Continuous-Time Representation Learning on Temporal Heterogeneous Information Network","created":"2024-05-11","cited_by_count":2,"area":null},{"id":"2412.20256","title":"Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours","created":"2024-12-28","cited_by_count":2,"area":null},{"id":"2510.23577","title":"TAMI: Taming Heterogeneity in Temporal Interactions for Temporal Graph Link Prediction","created":"2025-10-23","cited_by_count":2,"area":null},{"id":"2510.25348","title":"From Leakage to Fidelity: Reliable Benchmarking for Temporal Cascade Prediction","created":"2025-10-29","cited_by_count":2,"area":null},{"id":"2301.08399","title":"Who Should I Engage with At What Time? A Missing Event Aware Temporal Graph Neural Network","created":"2023-01-20","cited_by_count":1,"area":null},{"id":"2307.08433","title":"From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs","created":"2023-07-17","cited_by_count":1,"area":null},{"id":"2309.15875","title":"STAG: Enabling Low Latency and Low Staleness of GNN-based Services with Dynamic Graphs","created":"2023-09-27","cited_by_count":1,"area":null},{"id":"2509.00975","title":"Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning","created":"2025-08-31","cited_by_count":1,"area":null},{"id":"2110.13596","title":"TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation","created":"2021-10-26","cited_by_count":0,"area":null},{"id":"2203.01820","title":"An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022","created":"2022-03-01","cited_by_count":0,"area":null},{"id":"2304.05749","title":"Boosting long-term forecasting performance for continuous-time dynamic graph networks via data augmentation","created":"2023-04-12","cited_by_count":0,"area":"wm"},{"id":"2311.16605","title":"LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning","created":"2023-11-28","cited_by_count":0,"area":null},{"id":"2402.08918","title":"SimMLP: Training MLPs on Graphs without Supervision","created":"2024-02-14","cited_by_count":0,"area":null},{"id":"2407.07712","title":"Deep-Graph-Sprints: Accelerated Representation Learning in Continuous-Time Dynamic Graphs","created":"2024-07-10","cited_by_count":0,"area":null},{"id":"2507.07138","title":"GNNs Meet Sequence Models Along the Shortest-Path: an Expressive Method for Link Prediction","created":"2025-07-09","cited_by_count":0,"area":null},{"id":"2507.13825","title":"When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction","created":"2025-07-18","cited_by_count":0,"area":null},{"id":"2510.05569","title":"Efficient Learning-based Graph Simulation for Temporal Graphs","created":"2025-10-07","cited_by_count":0,"area":null},{"id":"2511.00047","title":"DynBERG: Dynamic BERT-based Graph neural network for financial fraud detection","created":"2025-10-28","cited_by_count":0,"area":null},{"id":"2601.22427","title":"CoDCL: Counterfactual-Inspired Augmentation Contrastive Learning for Temporal Link Prediction in Social Networks","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2602.12613","title":"Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2602.17071","title":"AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation","created":"2026-02-19","cited_by_count":0,"area":null},{"id":"2603.03963","title":"TFWaveFormer: Temporal-Frequency Collaborative Multi-level Wavelet Transformer for Dynamic Link Prediction","created":"2026-03-04","cited_by_count":0,"area":null},{"id":"2605.16112","title":"Attention Dispersion in Dynamic Graph Transformers: Diagnosis and a Transferable Fix","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2605.25548","title":"SiST-GNN: Simultaneous Spatial-Temporal Message Passing for Dynamic Graph Representation Learning","created":"2026-05-25","cited_by_count":0,"area":null},{"id":"2606.22180","title":"FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism","created":"2026-06-20","cited_by_count":0,"area":null},{"id":"2608.17987","title":"Against Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Media","created":"2026-08-18","cited_by_count":0,"area":null}],"next_cursor":null}