{"list":"other","total":54,"rows":[{"id":"1710.10903","title":"Graph Attention Networks","created":"2017-10-30","cited_by_count":8923},{"id":"1807.03748","title":"Representation Learning with Contrastive Predictive Coding","created":"2018-07-10","cited_by_count":7777},{"id":"1706.02216","title":"Inductive Representation Learning on Large Graphs","created":"2017-06-07","cited_by_count":6320},{"id":"1901.00596","title":"A Comprehensive Survey on Graph Neural Networks","created":"2019-01-03","cited_by_count":2919},{"id":"2002.02126","title":"LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation","created":"2020-02-06","cited_by_count":1139},{"id":"1707.08114","title":"A Survey on Multi-Task Learning","created":"2017-07-25","cited_by_count":840},{"id":"2105.14491","title":"How Attentive are Graph Attention Networks?","created":"2021-05-30","cited_by_count":835},{"id":"2006.08218","title":"Self-supervised Learning: Generative or Contrastive","created":"2020-06-15","cited_by_count":694},{"id":"1905.08108","title":"Neural Graph Collaborative Filtering","created":"2019-05-20","cited_by_count":661},{"id":"2011.00362","title":"A Survey on Contrastive Self-supervised Learning","created":"2020-10-31","cited_by_count":554},{"id":"2011.02260","title":"Graph Neural Networks in Recommender Systems: A Survey","created":"2020-11-04","cited_by_count":494},{"id":"1809.09401","title":"Hypergraph Neural Networks","created":"2018-09-25","cited_by_count":488},{"id":"1712.09482","title":"Robust Loss Functions under Label Noise for Deep Neural Networks","created":"2017-12-27","cited_by_count":443},{"id":"1905.07854","title":"KGAT: Knowledge Graph Attention Network for Recommendation","created":"2019-05-20","cited_by_count":343},{"id":"2010.10783","title":"Self-supervised Graph Learning for Recommendation","created":"2020-10-21","cited_by_count":305},{"id":"2103.00111","title":"Graph Self-Supervised Learning: A Survey","created":"2021-02-27","cited_by_count":289},{"id":"1806.05500","title":"Statistical Aspects of Wasserstein Distances","created":"2018-06-14","cited_by_count":203},{"id":"1811.01057","title":"Semidefinite relaxations for certifying robustness to adversarial examples","created":"2018-11-02","cited_by_count":179},{"id":"2112.08679","title":"Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation","created":"2021-12-16","cited_by_count":173},{"id":"2109.12843","title":"A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions","created":"2021-09-27","cited_by_count":144},{"id":"1904.12575","title":"Knowledge Graph Convolutional Networks for Recommender Systems","created":"2019-03-18","cited_by_count":121},{"id":"2110.05730","title":"Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation","created":"2021-10-12","cited_by_count":121},{"id":"2001.10167","title":"Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach","created":"2020-01-28","cited_by_count":120},{"id":"2007.01764","title":"Disentangled Graph Collaborative Filtering","created":"2020-07-03","cited_by_count":118},{"id":"2203.15876","title":"Self-Supervised Learning for Recommender Systems: A Survey","created":"2022-03-29","cited_by_count":95},{"id":"2202.06200","title":"Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning","created":"2022-02-13","cited_by_count":86},{"id":"2207.00419","title":"Self-Supervised Learning for Videos: A Survey","created":"2022-06-18","cited_by_count":85},{"id":"2010.00130","title":"Computing Graph Neural Networks: A Survey from Algorithms to Accelerators","created":"2020-09-30","cited_by_count":81},{"id":"2012.06852","title":"Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation","created":"2020-12-12","cited_by_count":75},{"id":"2302.08191","title":"LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation","created":"2023-02-16","cited_by_count":72},{"id":"2205.00976","title":"Knowledge Graph Contrastive Learning for Recommendation","created":"2022-05-02","cited_by_count":70},{"id":"2303.13948","title":"Knowledge Graphs: Opportunities and Challenges","created":"2023-03-24","cited_by_count":70},{"id":"1809.03568","title":"Improving Question Answering by Commonsense-Based Pre-Training","created":"2018-09-05","cited_by_count":66},{"id":"2204.12200","title":"Hypergraph Contrastive Collaborative Filtering","created":"2022-04-26","cited_by_count":63},{"id":"2209.02544","title":"XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation","created":"2022-09-06","cited_by_count":57},{"id":"2105.07536","title":"Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data","created":"2021-05-16","cited_by_count":55},{"id":"2102.07952","title":"A Survey of Machine Learning for Computer Architecture and Systems","created":"2021-02-16","cited_by_count":53},{"id":"2201.04309","title":"Robust Contrastive Learning against Noisy Views","created":"2022-01-12","cited_by_count":45},{"id":"2303.07797","title":"Automated Self-Supervised Learning for Recommendation","created":"2023-03-14","cited_by_count":37},{"id":"2211.15055","title":"AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning","created":"2022-11-28","cited_by_count":31},{"id":"2305.10837","title":"Adaptive Graph Contrastive Learning for Recommendation","created":"2023-05-18","cited_by_count":31},{"id":"2306.02330","title":"Graph Transformer for Recommendation","created":"2023-06-04","cited_by_count":28},{"id":"2104.07892","title":"Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks","created":"2021-04-16","cited_by_count":22},{"id":"2305.02759","title":"Disentangled Contrastive Collaborative Filtering","created":"2023-05-04","cited_by_count":22},{"id":"2210.10321","title":"Efficient Bi-Level Optimization for Recommendation Denoising","created":"2022-10-19","cited_by_count":20},{"id":"2307.05100","title":"Generative Contrastive Graph Learning for Recommendation","created":"2023-07-11","cited_by_count":20},{"id":"2205.14837","title":"Enhancing Sequential Recommendation with Graph Contrastive Learning","created":"2022-05-30","cited_by_count":18},{"id":"2302.05862","title":"Denoising and Prompt-Tuning for Multi-Behavior Recommendation","created":"2023-02-12","cited_by_count":18},{"id":"2303.08346","title":"Robust Preference-Guided Denoising for Graph based Social Recommendation","created":"2023-03-15","cited_by_count":15},{"id":"2303.09902","title":"Contrastive Self-supervised Learning in Recommender Systems: A Survey","created":"2023-03-17","cited_by_count":14},{"id":"2209.01347","title":"Explanation Guided Contrastive Learning for Sequential Recommendation","created":"2022-09-03","cited_by_count":11},{"id":"2401.15635","title":"RecDCL: Dual Contrastive Learning for Recommendation","created":"2024-01-28","cited_by_count":11},{"id":"2403.11136","title":"Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation","created":"2024-03-17","cited_by_count":8},{"id":"2406.13996","title":"Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering","created":"2024-06-20","cited_by_count":2}],"next_cursor":null}