{"total":29,"rows":[{"id":"2504.12722","title":"SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation","created":"2025-04-17","cited_by_count":33,"area":null},{"id":"2205.11127","title":"Fairness in Recommender Systems: Research Landscape and Future Directions","created":"2022-05-23","cited_by_count":30,"area":null},{"id":"2410.03432","title":"EB-NeRD: A Large-Scale Dataset for News Recommendation","created":"2024-10-04","cited_by_count":12,"area":null},{"id":"2206.00407","title":"Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems","created":"2022-06-01","cited_by_count":9,"area":null},{"id":"2403.00817","title":"Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random","created":"2024-02-26","cited_by_count":7,"area":null},{"id":"2203.05952","title":"Balancing Consumer and Business Value of Recommender Systems: A Simulation-based Analysis","created":"2022-03-10","cited_by_count":6,"area":null},{"id":"2206.11338","title":"Synthetic Data-Based Simulators for Recommender Systems: A Survey","created":"2022-06-22","cited_by_count":5,"area":null},{"id":"2303.05812","title":"Semi-supervised Adversarial Learning for Complementary Item Recommendation","created":"2023-03-10","cited_by_count":5,"area":null},{"id":"2412.03620","title":"Recommender Systems for Sustainability: Overview and Research Issues","created":"2024-12-04","cited_by_count":5,"area":null},{"id":"2108.05390","title":"Seven challenges for harmonizing explainability requirements","created":"2021-08-11","cited_by_count":4,"area":null},{"id":"2108.11068","title":"Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation","created":"2021-08-25","cited_by_count":4,"area":null},{"id":"2207.06225","title":"Sequential Recommendation Model for Next Purchase Prediction","created":"2022-07-06","cited_by_count":3,"area":null},{"id":"2509.05460","title":"Calibrated Recommendations with Contextual Bandits","created":"2025-09-05","cited_by_count":3,"area":null},{"id":"2402.03481","title":"FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning","created":"2024-02-05","cited_by_count":2,"area":null},{"id":"2411.16645","title":"Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that Matters","created":"2024-11-25","cited_by_count":2,"area":null},{"id":"2603.28476","title":"With a Little Help From My Friends: Collective Manipulation in Risk-Controlling Recommender Systems","created":"2026-03-30","cited_by_count":2,"area":null},{"id":"2107.06630","title":"Online Evaluation Methods for the Causal Effect of Recommendations","created":"2021-07-14","cited_by_count":1,"area":null},{"id":"2210.10309","title":"Multi-Objective Recommender Systems: Survey and Challenges","created":"2022-10-19","cited_by_count":1,"area":null},{"id":"2408.00312","title":"Adversarial Text Rewriting for Text-aware Recommender Systems","created":"2024-08-01","cited_by_count":1,"area":null},{"id":"2408.05353","title":"IntentRec: Predicting User Session Intent with Hierarchical Multi-Task Learning","created":"2024-07-25","cited_by_count":1,"area":null},{"id":"2508.15262","title":"M-$LLM^3$REC: A Motivation-Aware User-Item Interaction Framework for Enhancing Recommendation Accuracy with LLMs","created":"2025-08-21","cited_by_count":1,"area":null},{"id":"2302.02579","title":"Recommender Systems: A Primer","created":"2023-02-06","cited_by_count":0,"area":null},{"id":"2402.08109","title":"From Data to Decisions: The Transformational Power of Machine Learning in Business Recommendations","created":"2024-02-12","cited_by_count":0,"area":null},{"id":"2407.04472","title":"EventChat: Implementation and user-centric evaluation of a large language model-driven conversational recommender system for exploring leisure events in an SME context","created":"2024-07-05","cited_by_count":0,"area":null},{"id":"2409.07627","title":"Leveraging User-Generated Reviews for Recommender Systems with Dynamic Headers","created":"2024-09-11","cited_by_count":0,"area":null},{"id":"2507.09566","title":"Identifying Offline Metrics that Predict Online Impact: A Pragmatic Strategy for Real-World Recommender Systems","created":"2025-07-13","cited_by_count":0,"area":null},{"id":"2510.09136","title":"Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2602.08886","title":"Contrastive Learning for Diversity-Aware Product Recommendations in Retail","created":"2026-02-09","cited_by_count":0,"area":null},{"id":"2607.10915","title":"Normative Alignment of Recommender Systems via Internal Label Shift","created":"2026-07-12","cited_by_count":0,"area":null}],"next_cursor":null}