{"total":40,"rows":[{"id":"2201.06820","title":"Recommendation Unlearning","created":"2022-01-18","cited_by_count":80,"area":null},{"id":"2104.13030","title":"A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation","created":"2021-04-27","cited_by_count":59,"area":null},{"id":"2101.03392","title":"Generate Natural Language Explanations for Recommendation","created":"2021-01-09","cited_by_count":23,"area":null},{"id":"2204.01499","title":"FedRecAttack: Model Poisoning Attack to Federated Recommendation","created":"2022-04-01","cited_by_count":20,"area":null},{"id":"2109.12509","title":"Deep Exploration for Recommendation Systems","created":"2021-09-26","cited_by_count":14,"area":null},{"id":"2206.11549","title":"Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling","created":"2022-06-23","cited_by_count":14,"area":null},{"id":"2204.13594","title":"Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios","created":"2022-04-26","cited_by_count":13,"area":null},{"id":"2209.15292","title":"The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm","created":"2022-09-30","cited_by_count":9,"area":null},{"id":"2409.01012","title":"Improved Diversity-Promoting Collaborative Metric Learning for Recommendation","created":"2024-09-02","cited_by_count":9,"area":null},{"id":"2304.02539","title":"Multi-annotator Deep Learning: A Probabilistic Framework for Classification","created":"2023-04-05","cited_by_count":8,"area":null},{"id":"2104.14200","title":"Learning Heterogeneous Temporal Patterns of User Preference for Timely Recommendation","created":"2021-04-29","cited_by_count":7,"area":null},{"id":"2109.00217","title":"Multi-Sample based Contrastive Loss for Top-k Recommendation","created":"2021-09-01","cited_by_count":7,"area":null},{"id":"2402.02855","title":"Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation","created":"2024-02-05","cited_by_count":7,"area":null},{"id":"2103.16103","title":"Local Collaborative Autoencoders","created":"2021-03-30","cited_by_count":5,"area":null},{"id":"2201.06759","title":"Knowledge Sharing via Domain Adaptation in Customs Fraud Detection","created":"2022-01-18","cited_by_count":5,"area":null},{"id":"2210.13686","title":"FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings","created":"2022-10-25","cited_by_count":4,"area":null},{"id":"2207.12660","title":"Bilateral Self-unbiased Learning from Biased Implicit Feedback","created":"2022-07-26","cited_by_count":3,"area":null},{"id":"2104.09967","title":"Multi-target prediction for dummies using two-branch neural networks","created":"2021-04-19","cited_by_count":2,"area":null},{"id":"2201.03158","title":"Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems","created":"2022-01-10","cited_by_count":2,"area":null},{"id":"2306.10028","title":"Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Prediction","created":"2023-06-05","cited_by_count":2,"area":null},{"id":"2102.02549","title":"Dual-embedding based Neural Collaborative Filtering for Recommender Systems","created":"2021-02-04","cited_by_count":1,"area":null},{"id":"2201.08150","title":"A Systematic Analysis on the Impact of Contextual Information on Point-of-Interest Recommendation","created":"2022-01-20","cited_by_count":1,"area":null},{"id":"2203.07463","title":"Simultaneous Learning of the Inputs and Parameters in Neural Collaborative Filtering","created":"2022-03-14","cited_by_count":1,"area":null},{"id":"2206.14647","title":"Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction","created":"2022-06-28","cited_by_count":1,"area":null},{"id":"2212.10030","title":"InterMulti:Multi-view Multimodal Interactions with Text-dominated Hierarchical High-order Fusion for Emotion Analysis","created":"2022-12-20","cited_by_count":1,"area":null},{"id":"2309.15418","title":"Automatic Feature Fairness in Recommendation via Adversaries","created":"2023-09-27","cited_by_count":1,"area":null},{"id":"2505.10900","title":"Tuning-Free LLM Can Build A Strong Recommender Under Sparse Connectivity And Knowledge Gap Via Extracting Intent","created":"2025-05-16","cited_by_count":1,"area":null},{"id":"2508.14911","title":"Personalized Recommendations via Active Utility-based Pairwise Sampling","created":"2025-08-12","cited_by_count":1,"area":null},{"id":"2103.06105","title":"BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism","created":"2021-03-10","cited_by_count":0,"area":null},{"id":"2106.10679","title":"A Comprehensive Review on Non-Neural Networks Collaborative Filtering Recommendation Systems","created":"2021-06-20","cited_by_count":0,"area":null},{"id":"2110.10205","title":"MultiHead MultiModal Deep Interest Recommendation Network","created":"2021-10-19","cited_by_count":0,"area":null},{"id":"2204.11602","title":"Broad Recommender System: An Efficient Nonlinear Collaborative Filtering Approach","created":"2022-04-20","cited_by_count":0,"area":null},{"id":"2208.14594","title":"One-class Recommendation Systems with the Hinge Pairwise Distance Loss and Orthogonal Representations","created":"2022-08-31","cited_by_count":0,"area":null},{"id":"2210.05662","title":"Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems","created":"2022-10-11","cited_by_count":0,"area":null},{"id":"2212.08661","title":"EffMulti: Efficiently Modeling Complex Multimodal Interactions for Emotion Analysis","created":"2022-12-16","cited_by_count":0,"area":null},{"id":"2312.03167","title":"Adaptive spectral graph wavelets for collaborative filtering","created":"2023-12-05","cited_by_count":0,"area":null},{"id":"2404.08829","title":"Measuring the Predictability of Recommender Systems using Structural Complexity Metrics","created":"2024-04-12","cited_by_count":0,"area":null},{"id":"2502.19271","title":"Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems","created":"2025-02-26","cited_by_count":0,"area":null},{"id":"2508.03518","title":"Parameter-Efficient Single Collaborative Branch for Recommendation","created":"2025-08-05","cited_by_count":0,"area":null},{"id":"2508.19620","title":"A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions","created":"2025-08-27","cited_by_count":0,"area":null}],"next_cursor":null}