Cover Image

Modeling User Exploration Saturation: When Recommender Systems Should Stop Pushing Novelty

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ayiku, Enock O., Osei, Evelyn, Onyeka, Emebo
Format:	Preprint
Published:	2026
Subjects:	Information Retrieval Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Session-based Recommender Systems: User Interest as a Stochastic Process in the Latent Space
by: Balcer, Klaudia, et al.
Published: (2025)

Bridging User Dynamics: Transforming Sequential Recommendations with Schrödinger Bridge and Diffusion Models
by: Xie, Wenjia, et al.
Published: (2024)

CADC: Encoding User-Item Interactions for Compressing Recommendation Model Training Data
by: Zarch, Hossein Entezari, et al.
Published: (2024)

Knowledge-Enhanced Recommendation with User-Centric Subgraph Network
by: Liu, Guangyi, et al.
Published: (2024)

Save, Revisit, Retain: A Scalable Framework for Enhancing User Retention in Large-Scale Recommender Systems
by: Jiang, Weijie, et al.
Published: (2025)

Modeling Churn in Recommender Systems with Aggregated Preferences
by: Keinan, Gur, et al.
Published: (2025)

Enhancing Cross-Market Recommendation System with Graph Isomorphism Networks: A Novel Approach to Personalized User Experience
by: Öztürk, Sümeyye, et al.
Published: (2024)

Navigating the Future of Federated Recommendation Systems with Foundation Models
by: Li, Zhiwei, et al.
Published: (2024)

A Survey of Latent Factor Models in Recommender Systems
by: Alshbanat, Hind I., et al.
Published: (2024)

Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
by: Han, Xiao, et al.
Published: (2024)

Impression-Aware Recommender Systems
by: Maurera, Fernando B. Pérez, et al.
Published: (2023)

Large Language Models as Recommender Systems: A Study of Popularity Bias
by: Lichtenberg, Jan Malte, et al.
Published: (2024)

Heterogeneous Influence Maximization in User Recommendation
by: Hou, Hongru, et al.
Published: (2025)

When Relevance Meets Novelty: Dual-Stable Periodic Optimization for Serendipitous Recommendation
by: Lin, Hongxiang, et al.
Published: (2025)

Machine Unlearning for Recommendation Systems: An Insight
by: Sachdeva, Bhavika, et al.
Published: (2024)

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
by: Shao, Junli, et al.
Published: (2025)

A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems
by: Yuan, Jun, et al.
Published: (2024)

Review of Explainable Graph-Based Recommender Systems
by: Markchom, Thanet, et al.
Published: (2024)

A Survey on Popularity Bias in Recommender Systems
by: Klimashevskaia, Anastasiia, et al.
Published: (2023)

Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications
by: Lin, Ethan, et al.
Published: (2024)

Talos: Optimizing Top-$K$ Accuracy in Recommender Systems
by: Zhang, Shengjia, et al.
Published: (2026)

Extracting Interaction-Aware Monosemantic Concepts in Recommender Systems
by: Arviv, Dor, et al.
Published: (2025)

Ripple Knowledge Graph Convolutional Networks For Recommendation Systems
by: Li, Chen, et al.
Published: (2023)

Robust Reinforcement Learning Objectives for Sequential Recommender Systems
by: Mozifian, Melissa, et al.
Published: (2023)

A Comprehensive Survey of Evaluation Techniques for Recommendation Systems
by: Jadon, Aryan, et al.
Published: (2023)

Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn)
by: Bhattacharya, Moumita, et al.
Published: (2024)

PSLF: A PID Controller-incorporated Second-order Latent Factor Analysis Model for Recommender System
by: Wang, Jialiang, et al.
Published: (2024)

ArXivBench: When You Should Avoid Using ChatGPT for Academic Writing
by: Li, Ning, et al.
Published: (2025)

Large Language Model Distilling Medication Recommendation Model
by: Liu, Qidong, et al.
Published: (2024)

LLMs for User Interest Exploration in Large-scale Recommendation Systems
by: Wang, Jianling, et al.
Published: (2024)

BPL: Bias-adaptive Preference Distillation Learning for Recommender System
by: Kang, SeongKu, et al.
Published: (2025)

Weightless Neural Networks for Continuously Trainable Personalized Recommendation Systems
by: Latif, Rafayel, et al.
Published: (2025)

CADMR: Cross-Attention and Disentangled Learning for Multimodal Recommender Systems
by: Khalafaoui, Yasser, et al.
Published: (2024)

Modeling Behavioral Intensity and Transitions for Generative Recommendation
by: Yang, Wenxuan, et al.
Published: (2026)

Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
by: Wilm, Timo, et al.
Published: (2024)

Mem-Rec: Memory Efficient Recommendation System using Alternative Representation
by: Jha, Gopi Krishna, et al.
Published: (2023)

DiffGRM: Diffusion-based Generative Recommendation Model
by: Liu, Zhao, et al.
Published: (2025)

Large Language Models for Next Point-of-Interest Recommendation
by: Li, Peibo, et al.
Published: (2024)

Graph Foundation Models for Recommendation: A Comprehensive Survey
by: Wu, Bin, et al.
Published: (2025)

Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention
by: Xu, Rengan, et al.
Published: (2024)