Cover Image

A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yuan, Jun, Cai, Guohao, Dong, Zhenhua
Format:	Preprint
Published:	2024
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

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

Improving One-class Recommendation with Multi-tasking on Various Preference Intensities
by: Shao, Chu-Jen, et al.
Published: (2024)

Enhancing Learning Path Recommendation via Multi-task Learning
by: Nasrin, Afsana, et al.
Published: (2025)

A Contextual-Aware Position Encoding for Sequential Recommendation
by: Yuan, Jun, et al.
Published: (2025)

Breaking the Top-$K$ Barrier: Advancing Top-$K$ Ranking Metrics Optimization in Recommender Systems
by: Yang, Weiqin, et al.
Published: (2025)

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

RL-MPCA: A Reinforcement Learning Based Multi-Phase Computation Allocation Approach for Recommender Systems
by: Zhou, Jiahong, et al.
Published: (2023)

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

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

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

Advancing Cultural Inclusivity: Optimizing Embedding Spaces for Balanced Music Recommendations
by: Moradi, Armin, et al.
Published: (2024)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation
by: Liang, Mingfu, et al.
Published: (2025)

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

Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation
by: Huang, Tianhao, et al.
Published: (2024)

RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
by: Li, Shijun, et al.
Published: (2026)

RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations
by: Kruse, Johannes, et al.
Published: (2024)

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

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

Contextual Bandit with Herding Effects: Algorithms and Recommendation Applications
by: Xu, Luyue, et al.
Published: (2024)

Semantic Search and Recommendation Algorithm
by: Duhan, Aryan, et al.
Published: (2024)

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

Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking
by: Ramazanli, Ilqar, et al.
Published: (2025)

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

From Individual to Group: Developing a Context-Aware Multi-Criteria Group Recommender System
by: Le, Ngoc Luyen, et al.
Published: (2025)

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

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

STAR: A Simple Training-free Approach for Recommendations using Large Language Models
by: Lee, Dong-Ho, et al.
Published: (2024)

Modeling User Exploration Saturation: When Recommender Systems Should Stop Pushing Novelty
by: Ayiku, Enock O., et al.
Published: (2026)

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

Multi-Faceted Large Embedding Tables for Pinterest Ads Ranking
by: Su, Runze, et al.
Published: (2025)

Unifying Ranking and Generation in Query Auto-Completion via Retrieval-Augmented Generation and Multi-Objective Alignment
by: Yuan, Kai, et al.
Published: (2026)

LLaTTE: Scaling Laws for Multi-Stage Sequence Modeling in Large-Scale Ads Recommendation
by: Xiong, Lee, et al.
Published: (2026)

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation
by: Li, Shijun, et al.
Published: (2024)

Multi-Item-Query Attention for Stable Sequential Recommendation
by: Xu, Mingshi, et al.
Published: (2025)

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

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

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

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)

Enhancing Personalized Recipe Recommendation Through Multi-Class Classification
by: Neelam, Harish, et al.
Published: (2024)