Deep Pareto Reinforcement Learning for Multi-Objective Recommender Systems
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Pan, Tuzhilin, Alexander |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Pareto-based Multi-Objective Recommender System with Forgetting Curve
by: Jin, Jipeng, et al.
Published: (2023)
by: Jin, Jipeng, et al.
Published: (2023)
Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
by: Wilm, Timo, et al.
Published: (2024)
by: Wilm, Timo, et al.
Published: (2024)
Joint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier
by: Rampisela, Theresia Veronika, et al.
Published: (2025)
by: Rampisela, Theresia Veronika, et al.
Published: (2025)
Robust Reinforcement Learning Objectives for Sequential Recommender Systems
by: Mozifian, Melissa, et al.
Published: (2023)
by: Mozifian, Melissa, et al.
Published: (2023)
ACT: Automated Constraint Targeting for Multi-Objective Recommender Systems
by: Chang, Daryl, et al.
Published: (2025)
by: Chang, Daryl, et al.
Published: (2025)
Curr-RLCER:Curriculum Reinforcement Learning For Coherence Explainable Recommendation
by: Pan, Xiangchen, et al.
Published: (2026)
by: Pan, Xiangchen, et al.
Published: (2026)
Multi-Objective Recommendation via Multivariate Policy Learning
by: Jeunen, Olivier, et al.
Published: (2024)
by: Jeunen, Olivier, et al.
Published: (2024)
ICPE: An Item Cluster-Wise Pareto-Efficient Framework for Recommendation Debiasing
by: Wang, Yule, et al.
Published: (2021)
by: Wang, Yule, et al.
Published: (2021)
Future-Conditioned Recommendations with Multi-Objective Controllable Decision Transformer
by: Gao, Chongming, et al.
Published: (2025)
by: Gao, Chongming, et al.
Published: (2025)
FedSlate:A Federated Deep Reinforcement Learning Recommender System
by: Deng, Yongxin, et al.
Published: (2024)
by: Deng, Yongxin, et al.
Published: (2024)
Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
by: Liu, Langming, et al.
Published: (2025)
by: Liu, Langming, et al.
Published: (2025)
Deep Research for Recommender Systems
by: Ou, Kesha, et al.
Published: (2026)
by: Ou, Kesha, et al.
Published: (2026)
Goal-Conditioned Supervised Learning for Multi-Objective Recommendation
by: Li, Shijun, et al.
Published: (2024)
by: Li, Shijun, et al.
Published: (2024)
Self-Distilled Reinforcement Learning for Co-Evolving Agentic Recommender Systems
by: Wang, Zongwei, et al.
Published: (2026)
by: Wang, Zongwei, et al.
Published: (2026)
Retrieval-GRPO: A Multi-Objective Reinforcement Learning Framework for Dense Retrieval in Taobao Search
by: Liu, Xingxian, et al.
Published: (2025)
by: Liu, Xingxian, et al.
Published: (2025)
Rank-GRPO: Training LLM-based Conversational Recommender Systems with Reinforcement Learning
by: Zhu, Yaochen, et al.
Published: (2025)
by: Zhu, Yaochen, et al.
Published: (2025)
Reformulating Conversational Recommender Systems as Tri-Phase Offline Policy Learning
by: Zhang, Gangyi, et al.
Published: (2024)
by: Zhang, Gangyi, et al.
Published: (2024)
xMTF: A Formula-Free Model for Reinforcement-Learning-Based Multi-Task Fusion in Recommender Systems
by: Cao, Yang, et al.
Published: (2025)
by: Cao, Yang, 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)
Towards Multi-Behavior Multi-Task Recommendation via Behavior-informed Graph Embedding Learning
by: Lai, Wenhao, et al.
Published: (2026)
by: Lai, Wenhao, et al.
Published: (2026)
A Survey on Multi-Behavior Sequential Recommendation
by: Chen, Xiaoqing, et al.
Published: (2023)
by: Chen, Xiaoqing, et al.
Published: (2023)
MODRL-TA:A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search
by: Cheng, Peng, et al.
Published: (2024)
by: Cheng, Peng, et al.
Published: (2024)
DARLR: Dual-Agent Offline Reinforcement Learning for Recommender Systems with Dynamic Reward
by: Zhang, Yi, et al.
Published: (2025)
by: Zhang, Yi, et al.
Published: (2025)
Pairwise Ranking Loss for Multi-Task Learning in Recommender Systems
by: Durmus, Furkan, et al.
Published: (2024)
by: Durmus, Furkan, et al.
Published: (2024)
Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System
by: Pan, Yunzhu, et al.
Published: (2023)
by: Pan, Yunzhu, et al.
Published: (2023)
UNEX-RL: Reinforcing Long-Term Rewards in Multi-Stage Recommender Systems with UNidirectional EXecution
by: Zhang, Gengrui, et al.
Published: (2024)
by: Zhang, Gengrui, et al.
Published: (2024)
Multi-Objective Recommendation in the Era of Generative AI: A Survey of Recent Progress and Future Prospects
by: Hong, Zihan, et al.
Published: (2025)
by: Hong, Zihan, et al.
Published: (2025)
Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets
by: Bobadilla, Jesús, et al.
Published: (2024)
by: Bobadilla, Jesús, et al.
Published: (2024)
Retrieval Augmented Conversational Recommendation with Reinforcement Learning
by: Yue, Zhenrui, et al.
Published: (2026)
by: Yue, Zhenrui, et al.
Published: (2026)
AEFS: Adaptive Early Feature Selection for Deep Recommender Systems
by: Hu, Fan, et al.
Published: (2025)
by: Hu, Fan, et al.
Published: (2025)
MOReGIn: Multi-Objective Recommendation at the Global and Individual Levels
by: Gómez, Elizabeth, et al.
Published: (2024)
by: Gómez, Elizabeth, et al.
Published: (2024)
Objective Shaping with Hard Negatives: Windowed Partial AUC Optimization for RL-based LLM Recommenders
by: Shi, Wentao, et al.
Published: (2026)
by: Shi, Wentao, et al.
Published: (2026)
Multi-Cause Deconfounding for Recommender Systems with Latent Confounders
by: Huang, Zhirong, et al.
Published: (2024)
by: Huang, Zhirong, et al.
Published: (2024)
EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systems
by: Liu, Peng, et al.
Published: (2024)
by: Liu, Peng, et al.
Published: (2024)
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling
by: Wang, Jie, et al.
Published: (2024)
by: Wang, Jie, et al.
Published: (2024)
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)
Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation
by: Qu, Liang, et al.
Published: (2025)
by: Qu, Liang, et al.
Published: (2025)
Rankformer: A Graph Transformer for Recommendation based on Ranking Objective
by: Chen, Sirui, et al.
Published: (2025)
by: Chen, Sirui, et al.
Published: (2025)
MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
by: Wang, Lin, et al.
Published: (2026)
by: Wang, Lin, et al.
Published: (2026)
A Production-Ready RL Framework for Personalized Utility Tuning with Pareto Sweeping in Pinterest Recommender Systems
by: Zhou, Yichu, et al.
Published: (2026)
by: Zhou, Yichu, et al.
Published: (2026)
Similar Items
-
Pareto-based Multi-Objective Recommender System with Forgetting Curve
by: Jin, Jipeng, et al.
Published: (2023) -
Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
by: Wilm, Timo, et al.
Published: (2024) -
Joint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier
by: Rampisela, Theresia Veronika, et al.
Published: (2025) -
Robust Reinforcement Learning Objectives for Sequential Recommender Systems
by: Mozifian, Melissa, et al.
Published: (2023) -
ACT: Automated Constraint Targeting for Multi-Objective Recommender Systems
by: Chang, Daryl, et al.
Published: (2025)