Cover Image

The Unfairness of Multifactorial Bias in Recommendation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mansoury, Masoud, Huang, Jin, Pechenizkiy, Mykola, van Hoof, Herke, de Rijke, Maarten
Format:	Preprint
Published:	2026
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems
by: Huang, Jin, et al.
Published: (2024)

Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits
by: Mansoury, Masoud, et al.
Published: (2024)

Correcting Popularity Bias in Recommender Systems via Item Loss Equalization
by: Prent, Juno, et al.
Published: (2024)

Opening the Black Box: Interpretable Remedies for Popularity Bias in Recommender Systems
by: Ahmadov, Parviz, et al.
Published: (2025)

From Insight to Intervention: Interpretable Neuron Steering for Controlling Popularity Bias in Recommender Systems
by: Ahmadov, Parviz, et al.
Published: (2026)

Mitigating Popularity Bias in Counterfactual Explanations using Large Language Models
by: Hasami, Arjan, et al.
Published: (2025)

A Reproducibility Study of Product-side Fairness in Bundle Recommendation
by: Nguyen, Huy-Son, et al.
Published: (2025)

A First Look at Selection Bias in Preference Elicitation for Recommendation
by: Gupta, Shashank, et al.
Published: (2024)

Towards Carbon Footprint-Aware Recommender Systems for Greener Item Recommendation
by: Kalisvaart, Raoul, et al.
Published: (2025)

Revisiting Language Models in Neural News Recommender Systems
by: Zhao, Yuyue, et al.
Published: (2025)

Effectiveness of LLMs in Temporal User Profiling for Recommendation
by: Sabouri, Milad, et al.
Published: (2025)

Using LLMs to Capture Users' Temporal Context for Recommendation
by: Sabouri, Milad, et al.
Published: (2025)

ERASE -- A Real-World Aligned Benchmark for Unlearning in Recommender Systems
by: Lubitzsch, Pierre, et al.
Published: (2026)

Temporal User Profiling with LLMs: Balancing Short-Term and Long-Term Preferences for Recommendations
by: Sabouri, Milad, et al.
Published: (2025)

The Impact of Group Membership Bias on the Quality and Fairness of Exposure in Ranking
by: Vardasbi, Ali, et al.
Published: (2023)

Repeat-bias-aware Optimization of Beyond-accuracy Metrics for Next Basket Recommendation
by: Liu, Yuanna, et al.
Published: (2025)

Towards a Real-World Aligned Benchmark for Unlearning in Recommender Systems
by: Lubitzsch, Pierre, et al.
Published: (2025)

Contrastive Learning for Diversity-Aware Product Recommendations in Retail
by: Karlis, Vasileios, et al.
Published: (2026)

Cold-Starts in Generative Recommendation: A Reproducibility Study
by: Zhang, Zhen, et al.
Published: (2026)

UFO: Unfair-to-Fair Evolving Mitigates Unfairness in LLM-based Recommender Systems via Self-Play Fine-tuning
by: Zhang, Jiaming, et al.
Published: (2025)

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank (Extended Abstract)
by: Hager, Philipp, et al.
Published: (2025)

Towards Two-Stage Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2025)

RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models
by: Heuss, Maria, et al.
Published: (2024)

SARDINE: A Simulator for Automated Recommendation in Dynamic and Interactive Environments
by: Deffayet, Romain, et al.
Published: (2023)

Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning
by: Zhao, Yuyue, et al.
Published: (2024)

Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation
by: Lin, Kun, et al.
Published: (2024)

Towards Explainable Temporal User Profiling with LLMs
by: Sabouri, Milad, et al.
Published: (2025)

Investigating and Mitigating Stereotype-aware Unfairness in LLM-based Recommendations
by: Zhao, Zihuai, et al.
Published: (2025)

Cognitive Biases in Large Language Models for News Recommendation
by: Lyu, Yougang, et al.
Published: (2024)

Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?
by: Li, Ming, et al.
Published: (2024)

Robust Information Retrieval
by: Liu, Yu-An, et al.
Published: (2024)

Understanding Visual Saliency of Outlier Items in Product Search
by: Sarvi, Fatemeh, et al.
Published: (2025)

Orcheo: A Modular Full-Stack Platform for Conversational Search
by: Jiang, Shaojie, et al.
Published: (2026)

Multi-Step Semantic Reasoning in Generative Retrieval
by: Dong, Steven, et al.
Published: (2026)

Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMs
by: Siro, Clemencia, et al.
Published: (2024)

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank
by: Hager, Philipp, et al.
Published: (2025)

Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)

Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)

Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees
by: Kang, Jingwei, et al.
Published: (2024)

Curriculum Approximate Unlearning for Session-based Recommendation
by: Yang, Liu, et al.
Published: (2025)