Copertina

xMTF: A Formula-Free Model for Reinforcement-Learning-Based Multi-Task Fusion in Recommender Systems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cao, Yang, Zhang, Changhao, Chen, Xiaoshuang, Zhan, Kaiqiao, Wang, Ben
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

UNEX-RL: Reinforcing Long-Term Rewards in Multi-Stage Recommender Systems with UNidirectional EXecution
di: Zhang, Gengrui, et al.
Pubblicazione: (2024)

Cache-Aware Reinforcement Learning in Large-Scale Recommender Systems
di: Chen, Xiaoshuang, et al.
Pubblicazione: (2024)

RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
di: Su, Shuo, et al.
Pubblicazione: (2024)

CREAD: A Classification-Restoration Framework with Error Adaptive Discretization for Watch Time Prediction in Video Recommender Systems
di: Sun, Jie, et al.
Pubblicazione: (2024)

Creator-Side Recommender System: Challenges, Designs, and Applications
di: Chen, Xiaoshuang, et al.
Pubblicazione: (2025)

Enhancing Playback Performance in Video Recommender Systems with an On-Device Gating and Ranking Framework
di: Yang, Yunfei, et al.
Pubblicazione: (2024)

EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systems
di: Liu, Peng, et al.
Pubblicazione: (2024)

UnifiedRL: A Reinforcement Learning Algorithm Tailored for Multi-Task Fusion in Large-Scale Recommender Systems
di: Liu, Peng, et al.
Pubblicazione: (2024)

Pairwise Ranking Loss for Multi-Task Learning in Recommender Systems
di: Durmus, Furkan, et al.
Pubblicazione: (2024)

Unleashing the Potential of Two-Tower Models: Diffusion-Based Cross-Interaction for Large-Scale Matching
di: Wang, Yihan, et al.
Pubblicazione: (2025)

Fusion Self-supervised Learning for Recommendation
di: Zhang, Yu, et al.
Pubblicazione: (2024)

Deep Pareto Reinforcement Learning for Multi-Objective Recommender Systems
di: Li, Pan, et al.
Pubblicazione: (2024)

S$^2$GR: Stepwise Semantic-Guided Reasoning in Latent Space for Generative Recommendation
di: Guo, Zihao, et al.
Pubblicazione: (2026)

LESER: Learning to Expand via Search Engine-feedback Reinforcement in e-Commerce
di: Zhang, Yipeng, et al.
Pubblicazione: (2025)

Effective Knowledge Transfer for Multi-Task Recommendation Models
di: Cai, Guohao, et al.
Pubblicazione: (2026)

MBGR: Multi-Business Prediction for Generative Recommendation at Meituan
di: Li, Changhao, et al.
Pubblicazione: (2026)

Towards End-to-End Alignment of User Satisfaction via Questionnaire in Video Recommendation
di: Li, Na, et al.
Pubblicazione: (2026)

From Local Indices to Global Identifiers: Generative Reranking for Recommender Systems via Global Action Space
di: Jia, Pengyue, et al.
Pubblicazione: (2026)

Causal Learning for Trustworthy Recommender Systems: A Survey
di: Li, Jin, et al.
Pubblicazione: (2024)

Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
di: Liu, Langming, et al.
Pubblicazione: (2025)

Sequence-level Semantic Representation Fusion for Recommender Systems
di: Xu, Lanling, et al.
Pubblicazione: (2024)

Self-Distilled Reinforcement Learning for Co-Evolving Agentic Recommender Systems
di: Wang, Zongwei, et al.
Pubblicazione: (2026)

Unleashing the Potential of Multi-Channel Fusion in Retrieval for Personalized Recommendations
di: Huang, Junjie, et al.
Pubblicazione: (2024)

Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling
di: Wang, Jie, et al.
Pubblicazione: (2024)

Paragon: Parameter Generation for Controllable Multi-Task Recommendation
di: Shen, Chenglei, et al.
Pubblicazione: (2024)

MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
di: Wang, Lin, et al.
Pubblicazione: (2026)

DARLR: Dual-Agent Offline Reinforcement Learning for Recommender Systems with Dynamic Reward
di: Zhang, Yi, et al.
Pubblicazione: (2025)

EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systems
di: Yu, Yuanqing, et al.
Pubblicazione: (2024)

Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
di: Shi, Tianhao, et al.
Pubblicazione: (2023)

Efficient Multi-Task Learning via Generalist Recommender
di: Wang, Luyang, et al.
Pubblicazione: (2025)

A Survey on Generative Recommendation: Data, Model, and Tasks
di: Hou, Min, et al.
Pubblicazione: (2025)

LLM-Guided Multi-View Hypergraph Learning for Human-Centric Explainable Recommendation
di: Chu, Zhixuan, et al.
Pubblicazione: (2024)

Content-Based Collaborative Generation for Recommender Systems
di: Wang, Yidan, et al.
Pubblicazione: (2024)

Towards Automated Model Design on Recommender Systems
di: Zhang, Tunhou, et al.
Pubblicazione: (2024)

PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems
di: Yang, Mingdai, et al.
Pubblicazione: (2025)

Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMs
di: Zhao, Chuang, et al.
Pubblicazione: (2024)

Rethinking Multi-objective Ranking Ensemble in Recommender System: From Score Fusion to Rank Consistency
di: Xia, Boyang, et al.
Pubblicazione: (2026)

GraphFusionSBR: Denoising Multi-Channel Graphs for Session-Based Recommendation
di: He, Jia-Xin, et al.
Pubblicazione: (2026)

Towards Multi-Behavior Multi-Task Recommendation via Behavior-informed Graph Embedding Learning
di: Lai, Wenhao, et al.
Pubblicazione: (2026)

Personalized Multi-task Training for Recommender System
di: Yang, Liangwei, et al.
Pubblicazione: (2024)