{"total":66,"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":"2202.02519","title":"Intent Contrastive Learning for Sequential Recommendation","created":"2022-02-05","cited_by_count":91,"area":null},{"id":"2304.05055","title":"A Comprehensive Survey on Deep Graph Representation Learning","created":"2023-04-11","cited_by_count":72,"area":null},{"id":"2307.08097","title":"EasyTPP: Towards Open Benchmarking Temporal Point Processes","created":"2023-07-16","cited_by_count":68,"area":null},{"id":"2201.06035","title":"Sequential Recommendation via Stochastic Self-Attention","created":"2022-01-16","cited_by_count":37,"area":null},{"id":"2207.07483","title":"A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation","created":"2022-07-15","cited_by_count":22,"area":null},{"id":"2410.04013","title":"Improving Temporal Link Prediction via Temporal Walk Matrix Projection","created":"2024-10-05","cited_by_count":21,"area":null},{"id":"2108.11883","title":"DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN","created":"2021-08-26","cited_by_count":19,"area":null},{"id":"2110.06388","title":"HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization","created":"2021-10-12","cited_by_count":13,"area":null},{"id":"2405.20878","title":"SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation","created":"2024-05-31","cited_by_count":12,"area":null},{"id":"2308.14355","title":"TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems","created":"2023-08-28","cited_by_count":11,"area":null},{"id":"2202.08391","title":"Graph Masked Autoencoders with Transformers","created":"2022-02-17","cited_by_count":10,"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":"2401.05975","title":"End-to-end Learnable Clustering for Intent Learning in Recommendation","created":"2024-01-11","cited_by_count":10,"area":null},{"id":"2407.20871","title":"Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction","created":"2024-07-30","cited_by_count":10,"area":null},{"id":"2407.20824","title":"DyGKT: Dynamic Graph Learning for Knowledge Tracing","created":"2024-07-30","cited_by_count":9,"area":null},{"id":"2204.05490","title":"Continuous-Time User Preference Modelling for Temporal Sets Prediction","created":"2022-04-12","cited_by_count":7,"area":null},{"id":"2303.12341","title":"EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning","created":"2023-03-22","cited_by_count":7,"area":null},{"id":"2206.08050","title":"Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation","created":"2022-06-16","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":"2410.22013","title":"Modeling Temporal Positive and Negative Excitation for Sequential Recommendation","created":"2024-10-29","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":"2203.15508","title":"Improving Contrastive Learning with Model Augmentation","created":"2022-03-25","cited_by_count":5,"area":null},{"id":"2204.10851","title":"Exploiting Session Information in BERT-based Session-aware Sequential Recommendation","created":"2022-04-22","cited_by_count":4,"area":null},{"id":"2208.00593","title":"Long Short-Term Preference Modeling for Continuous-Time Sequential Recommendation","created":"2022-08-01","cited_by_count":4,"area":null},{"id":"2305.03883","title":"SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds","created":"2023-05-06","cited_by_count":4,"area":null},{"id":"2305.10824","title":"Integrating Item Relevance in Training Loss for Sequential Recommender Systems","created":"2023-05-18","cited_by_count":4,"area":null},{"id":"2406.18470","title":"UniRec: A Dual Enhancement of Uniformity and Frequency in Sequential Recommendations","created":"2024-06-26","cited_by_count":4,"area":null},{"id":"2412.07382","title":"Temporal Linear Item-Item Model for Sequential Recommendation","created":"2024-12-10","cited_by_count":4,"area":null},{"id":"2505.04461","title":"A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities","created":"2025-05-07","cited_by_count":4,"area":null},{"id":"2601.21135","title":"TRACE: Trajectory Recovery for Continuous Mechanism Evolution in Causal Representation Learning","created":"2026-01-29","cited_by_count":4,"area":null},{"id":"2210.13572","title":"Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer","created":"2022-10-24","cited_by_count":3,"area":null},{"id":"2211.06394","title":"STAR: A Session-Based Time-Aware Recommender System","created":"2022-11-11","cited_by_count":3,"area":null},{"id":"2301.01737","title":"Episodes Discovery Recommendation with Multi-Source Augmentations","created":"2023-01-04","cited_by_count":3,"area":null},{"id":"2301.12197","title":"Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation","created":"2023-01-28","cited_by_count":3,"area":null},{"id":"2401.01243","title":"Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces","created":"2024-01-02","cited_by_count":3,"area":null},{"id":"2404.07223","title":"Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling","created":"2024-03-27","cited_by_count":3,"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":"2304.05492","title":"Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training","created":"2023-04-11","cited_by_count":2,"area":null},{"id":"2307.13165","title":"Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations","created":"2023-07-24","cited_by_count":2,"area":null},{"id":"2312.06145","title":"Proxy-based Item Representation for Attribute and Context-aware Recommendation","created":"2023-12-11","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":"2408.15371","title":"Temporal Graph Neural Network-Powered Paper Recommendation on Dynamic Citation Networks","created":"2024-08-27","cited_by_count":2,"area":null},{"id":"2502.08132","title":"SS4Rec: Continuous-Time Sequential Recommendation with State Space Models","created":"2025-02-12","cited_by_count":2,"area":null},{"id":"2509.13957","title":"Enhancing Time Awareness in Generative Recommendation","created":"2025-09-17","cited_by_count":2,"area":null},{"id":"2207.11776","title":"Incorporating Heterogeneous User Behaviors and Social Influences for Predictive Analysis","created":"2022-07-24","cited_by_count":1,"area":null},{"id":"2309.04802","title":"CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning","created":"2023-09-09","cited_by_count":1,"area":null},{"id":"2403.03993","title":"Personalized Negative Reservoir for Incremental Learning in Recommender Systems","created":"2024-03-06","cited_by_count":1,"area":null},{"id":"2412.13408","title":"Lightweight yet Fine-grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-account Sequential Recommendation","created":"2024-12-18","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":"2605.13540","title":"Decoupled and Divergence-Conditioned Prompt for Multi-domain Dynamic Graph Foundation Models","created":"2026-05-13","cited_by_count":1,"area":null},{"id":"2112.05914","title":"Leaping Through Time with Gradient-based Adaptation for Recommendation","created":"2021-12-11","cited_by_count":0,"area":null},{"id":"2206.06804","title":"Recommender Transformers with Behavior Pathways","created":"2022-06-13","cited_by_count":0,"area":null},{"id":"2208.13330","title":"Time-aware Self-Attention Meets Logic Reasoning in Recommender Systems","created":"2022-08-29","cited_by_count":0,"area":null},{"id":"2310.13249","title":"TempGNN: Temporal Graph Neural Networks for Dynamic Session-Based Recommendations","created":"2023-10-20","cited_by_count":0,"area":null},{"id":"2404.18214","title":"Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement","created":"2024-04-28","cited_by_count":0,"area":null},{"id":"2408.00326","title":"Exploiting Preferences in Loss Functions for Sequential Recommendation via Weak Transitivity","created":"2024-08-01","cited_by_count":0,"area":null},{"id":"2409.17402","title":"Enhancing Recommendation with Denoising Auxiliary Task","created":"2024-09-25","cited_by_count":0,"area":null},{"id":"2410.01367","title":"Towards Dynamic Graph Neural Networks with Provably High-Order Expressive Power","created":"2024-10-02","cited_by_count":0,"area":null},{"id":"2410.11464","title":"CoActionGraphRec: Sequential Multi-Interest Recommendations Using Co-Action Graphs","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2411.09181","title":"DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation","created":"2024-11-14","cited_by_count":0,"area":null},{"id":"2604.26247","title":"TimeMM: Time-as-Operator Spectral Filtering for Dynamic Multimodal Recommendation","created":"2026-04-29","cited_by_count":0,"area":null},{"id":"2607.09666","title":"Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2607.19802","title":"Zero-Observation User Reactivation with Gap-Driven Dimensional Gating","created":"2026-07-22","cited_by_count":0,"area":null},{"id":"2608.07158","title":"Edge Sparsification via Temporal Forman-Ricci Curvature for Dynamic Graph Learning","created":"2026-08-07","cited_by_count":0,"area":null}],"next_cursor":null}