Save, Revisit, Retain: A Scalable Framework for Enhancing User Retention in Large-Scale Recommender Systems
Fuente:
arXiv
Saved in:
| Main Authors: | Jiang, Weijie, Ordorica, Armando, Yang, Jaewon, Gudmundsson, Olafur, Tu, Yucheng, Duan, Huizhong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Warmer for Less: A Cost-Efficient Strategy for Cold-Start Recommendations at Pinterest
by: Ebrahimi, Saeed, et al.
Published: (2025)
by: Ebrahimi, Saeed, et al.
Published: (2025)
Retention Induced Biases in a Recommendation System with Heterogeneous Users
by: Ma, Shichao
Published: (2024)
by: Ma, Shichao
Published: (2024)
Enhancing New-item Fairness in Dynamic Recommender Systems
by: Guo, Huizhong, et al.
Published: (2025)
by: Guo, Huizhong, et al.
Published: (2025)
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
by: Xue, Zhenghai, et al.
Published: (2023)
by: Xue, Zhenghai, et al.
Published: (2023)
REG4Rec: Reasoning-Enhanced Generative Model for Large-Scale Recommendation Systems
by: Xing, Haibo, et al.
Published: (2025)
by: Xing, Haibo, et al.
Published: (2025)
Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems
by: Togashi, Riku, et al.
Published: (2024)
by: Togashi, Riku, et al.
Published: (2024)
UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems
by: Zhang, Changshuo, et al.
Published: (2024)
by: Zhang, Changshuo, et al.
Published: (2024)
Enhancing User Intent for Recommendation Systems via Large Language Models
by: Xu, Xiaochuan, et al.
Published: (2025)
by: Xu, Xiaochuan, et al.
Published: (2025)
Stratified Expert Cloning for Retention-Aware Recommendation at Scale
by: Lin, Chengzhi, et al.
Published: (2025)
by: Lin, Chengzhi, et al.
Published: (2025)
Reward Balancing Revisited: Enhancing Offline Reinforcement Learning for Recommender Systems
by: Shu, Wenzheng, et al.
Published: (2025)
by: Shu, Wenzheng, et al.
Published: (2025)
Bootstrapping Conditional Retrieval for User-to-Item Recommendations
by: Lin, Hongtao, et al.
Published: (2025)
by: Lin, Hongtao, et al.
Published: (2025)
Reinforce Lifelong Interaction Value of User-Author Pairs for Large-Scale Recommendation Systems
by: Li, Yisha, et al.
Published: (2025)
by: Li, Yisha, et al.
Published: (2025)
USD: A User-Intent-Driven Sampling and Dual-Debiasing Framework for Large-Scale Homepage Recommendations
by: Zheng, Jiaqi, et al.
Published: (2025)
by: Zheng, Jiaqi, et al.
Published: (2025)
Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention
by: Xu, Rengan, et al.
Published: (2024)
by: Xu, Rengan, et al.
Published: (2024)
Evaluating Conversational Recommender Systems via Large Language Models: A User-Centric Framework
by: Chen, Nuo, et al.
Published: (2025)
by: Chen, Nuo, et al.
Published: (2025)
Enhancing Playback Performance in Video Recommender Systems with an On-Device Gating and Ranking Framework
by: Yang, Yunfei, et al.
Published: (2024)
by: Yang, Yunfei, et al.
Published: (2024)
A Hybrid Recommendation Framework for Enhancing User Engagement in Local News
by: Pourashraf, Payam, et al.
Published: (2025)
by: Pourashraf, Payam, et al.
Published: (2025)
Unlocking Scaling Law in Industrial Recommendation Systems with a Three-step Paradigm based Large User Model
by: Yan, Bencheng, et al.
Published: (2025)
by: Yan, Bencheng, et al.
Published: (2025)
Modeling User Retention through Generative Flow Networks
by: Liu, Ziru, et al.
Published: (2024)
by: Liu, Ziru, et al.
Published: (2024)
Memento: Personalized RAG-Style Long-Retention Data Scaling for META Ads Recommendation
by: Chen, Xiaoyu, et al.
Published: (2026)
by: Chen, Xiaoyu, et al.
Published: (2026)
A Study on Enhancing User Engagement by Employing Gamified Recommender Systems
by: Fallahi, Ali, et al.
Published: (2025)
by: Fallahi, Ali, et al.
Published: (2025)
Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
by: Zhang, Hao, et al.
Published: (2023)
by: Zhang, Hao, et al.
Published: (2023)
A General Framework for Multimodal LLM-Based Multimedia Understanding in Large-Scale Recommendation Systems
by: Zhu, Yiming, et al.
Published: (2026)
by: Zhu, Yiming, et al.
Published: (2026)
Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation
by: Wei, Tianjun, et al.
Published: (2025)
by: Wei, Tianjun, et al.
Published: (2025)
Aggregate and Broadcast: Scalable and Efficient Feature Interaction for Recommender Systems
by: Li, Kaiyuan, et al.
Published: (2025)
by: Li, Kaiyuan, et al.
Published: (2025)
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention
by: Liu, Ziru, et al.
Published: (2024)
by: Liu, Ziru, et al.
Published: (2024)
Temporal-Aware User Behaviour Simulation with Large Language Models for Recommender Systems
by: Wanyan, Xinye, et al.
Published: (2025)
by: Wanyan, Xinye, et al.
Published: (2025)
User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems
by: Wang, Jianling, et al.
Published: (2025)
by: Wang, Jianling, et al.
Published: (2025)
Bending the Scaling Law Curve in Large-Scale Recommendation Systems
by: Ding, Qin, et al.
Published: (2026)
by: Ding, Qin, et al.
Published: (2026)
RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems
by: Chen, Jin, et al.
Published: (2026)
by: Chen, Jin, et al.
Published: (2026)
Measuring Fairness in Large-Scale Recommendation Systems with Missing Labels
by: Dong, Yulong, et al.
Published: (2024)
by: Dong, Yulong, et al.
Published: (2024)
MTGR: Industrial-Scale Generative Recommendation Framework in Meituan
by: Han, Ruidong, et al.
Published: (2025)
by: Han, Ruidong, et al.
Published: (2025)
Revisiting Language Models in Neural News Recommender Systems
by: Zhao, Yuyue, et al.
Published: (2025)
by: Zhao, Yuyue, et al.
Published: (2025)
Understand your Users, An Ensemble Learning Framework for Natural Noise Filtering in Recommender Systems
by: Hawat, Clarita, et al.
Published: (2025)
by: Hawat, Clarita, et al.
Published: (2025)
PinRec: Outcome-Conditioned, Multi-Token Generative Retrieval for Industry-Scale Recommendation Systems
by: Agarwal, Prabhat, et al.
Published: (2025)
by: Agarwal, Prabhat, et al.
Published: (2025)
The Role of Fake Users in Sequential Recommender Systems
by: Betello, Filippo
Published: (2024)
by: Betello, Filippo
Published: (2024)
Enhancing Recommendation Explanations through User-Centric Refinement
by: Zhang, Jingsen, et al.
Published: (2025)
by: Zhang, Jingsen, et al.
Published: (2025)
Dynamic User Interest Augmentation via Stream Clustering and Memory Networks in Large-Scale Recommender Systems
by: Liu, Peng, et al.
Published: (2024)
by: Liu, Peng, et al.
Published: (2024)
Enhancing Serendipity Recommendation System by Constructing Dynamic User Knowledge Graphs with Large Language Models
by: Yong, Qian, et al.
Published: (2025)
by: Yong, Qian, et al.
Published: (2025)
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
by: Wang, Yan, et al.
Published: (2023)
by: Wang, Yan, et al.
Published: (2023)
Similar Items
-
Warmer for Less: A Cost-Efficient Strategy for Cold-Start Recommendations at Pinterest
by: Ebrahimi, Saeed, et al.
Published: (2025) -
Retention Induced Biases in a Recommendation System with Heterogeneous Users
by: Ma, Shichao
Published: (2024) -
Enhancing New-item Fairness in Dynamic Recommender Systems
by: Guo, Huizhong, et al.
Published: (2025) -
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems
by: Xue, Zhenghai, et al.
Published: (2023) -
REG4Rec: Reasoning-Enhanced Generative Model for Large-Scale Recommendation Systems
by: Xing, Haibo, et al.
Published: (2025)