Image de couverture de livre

Bypassing the Popularity Bias: Repurposing Models for Better Long-Tail Recommendation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Blahut, Václav, Koupil, Karel
Format:	Preprint
Publié:	2024
Sujets:	Information Retrieval Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
par: Tan, Shiyin, et autres
Publié: (2025)

A Survey on Popularity Bias in Recommender Systems
par: Klimashevskaia, Anastasiia, et autres
Publié: (2023)

Large Language Models as Recommender Systems: A Study of Popularity Bias
par: Lichtenberg, Jan Malte, et autres
Publié: (2024)

Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems
par: Zhang, Jiaming, et autres
Publié: (2026)

Reducing Popularity Influence by Addressing Position Bias
par: Dzhoha, Andrii, et autres
Publié: (2024)

Listwise Preference Alignment Optimization for Tail Item Recommendation
par: Li, Zihao, et autres
Publié: (2025)

Recommendation Is a Dish Better Served Warm
par: Gusak, Danil, et autres
Publié: (2025)

Measuring Recency Bias In Sequential Recommendation Systems
par: Oh, Jeonglyul, et autres
Publié: (2024)

Evaluating Performance and Bias of Negative Sampling in Large-Scale Sequential Recommendation Models
par: Prakash, Arushi, et autres
Publié: (2024)

BiCoRec: Bias-Mitigated Context-Aware Sequential Recommendation Model
par: Muthivhi, Mufhumudzi, et autres
Publié: (2025)

Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering
par: Islam, Md Aminul, et autres
Publié: (2026)

Long-Sequence Recommendation Models Need Decoupled Embeddings
par: Feng, Ningya, et autres
Publié: (2024)

Algorithm Adaptation Bias in Recommendation System Online Experiments
par: Zheng, Chen, et autres
Publié: (2025)

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations
par: Singh, Anima, et autres
Publié: (2023)

Causality-aware Graph Aggregation Weight Estimator for Popularity Debiasing in Top-K Recommendation
par: Que, Yue, et autres
Publié: (2025)

CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems
par: Zhang, Haochen, et autres
Publié: (2025)

TranSUN: A Preemptive Paradigm to Eradicate Retransformation Bias Intrinsically from Regression Models in Recommender Systems
par: Yu, Jiahao, et autres
Publié: (2025)

Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline Evaluation
par: Pires, Pedro R., et autres
Publié: (2025)

Make It Long, Keep It Fast: End-to-End 10K Long User Behavior Sequence Modeling for Billion-Scale Douyin Recommendation
par: Guan, Lin, et autres
Publié: (2025)

Exploring Contrastive Learning for Long-Tailed Multi-Label Text Classification
par: Audibert, Alexandre, et autres
Publié: (2024)

When and What to Recommend: Joint Modeling of Timing and Content for Active Sequential Recommendation
par: Chai, Jin, et autres
Publié: (2025)

Debiased Model-based Interactive Recommendation
par: Li, Zijian, et autres
Publié: (2024)

Data Efficiency for Large Recommendation Models
par: Jain, Kshitij, et autres
Publié: (2024)

Neural Click Models for Recommender Systems
par: Shirokikh, Mikhail, et autres
Publié: (2024)

BPL: Bias-adaptive Preference Distillation Learning for Recommender System
par: Kang, SeongKu, et autres
Publié: (2025)

An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention
par: Shin, Yehjin, et autres
Publié: (2023)

Are Recommenders Self-Aware? Label-Free Recommendation Performance Estimation via Model Uncertainty
par: Li, Jiayu, et autres
Publié: (2025)

Modeling Attrition in Recommender Systems with Departing Bandits
par: Ben-Porat, Omer, et autres
Publié: (2022)

Multiple Models for Recommending Temporal Aspects of Entities
par: Nguyen, Tu, et autres
Publié: (2018)

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
par: Li, Haoxuan, et autres
Publié: (2024)

Temporal Linear Item-Item Model for Sequential Recommendation
par: Park, Seongmin, et autres
Publié: (2024)

On the Embedding Collapse when Scaling up Recommendation Models
par: Guo, Xingzhuo, et autres
Publié: (2023)

Hierarchical Group-wise Ranking Framework for Recommendation Models
par: Yan, YaChen, et autres
Publié: (2025)

GENPLUGIN: A Plug-and-Play Framework for Long-Tail Generative Recommendation with Exposure Bias Mitigation
par: Yang, Kun, et autres
Publié: (2025)

Enhancing Recommendation Diversity by Re-ranking with Large Language Models
par: Carraro, Diego, et autres
Publié: (2024)

Accelerating Recommender Model Training by Dynamically Skipping Stale Embeddings
par: Maboud, Yassaman Ebrahimzadeh, et autres
Publié: (2024)

Probabilistic Rank and Reward: A Scalable Model for Slate Recommendation
par: Aouali, Imad, et autres
Publié: (2022)

Cross-attention Secretly Performs Orthogonal Alignment in Recommendation Models
par: Lee, Hyunin, et autres
Publié: (2025)

On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective
par: Loveland, Donald, et autres
Publié: (2025)

Tail-Aware Data Augmentation for Long-Tail Sequential Recommendation
par: Dang, Yizhou, et autres
Publié: (2026)