Post-hoc Popularity Bias Correction in GNN-based Collaborative Filtering
Fuente:
arXiv
Guardado en:
| Autores principales: | Islam, Md Aminul, Zheleva, Elena, Wang, Ren |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering
por: Islam, Md Aminul, et al.
Publicado: (2026)
por: Islam, Md Aminul, et al.
Publicado: (2026)
Correcting for Position Bias in Learning to Rank: A Control Function Approach
por: Islam, Md Aminul, et al.
Publicado: (2025)
por: Islam, Md Aminul, et al.
Publicado: (2025)
Prompt-Based LLMs for Position Bias-Aware Reranking in Personalized Recommendations
por: Islam, Md Aminul, et al.
Publicado: (2025)
por: Islam, Md Aminul, et al.
Publicado: (2025)
Rethinking Popularity Bias in Collaborative Filtering via Analytical Vector Decomposition
por: Liu, Lingfeng, et al.
Publicado: (2025)
por: Liu, Lingfeng, et al.
Publicado: (2025)
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems
por: Huang, Jin, et al.
Publicado: (2024)
por: Huang, Jin, et al.
Publicado: (2024)
Utilizing Collaborative Filtering in a Personalized Research-Paper Recommendation System
por: Hasan, Mahamudul, et al.
Publicado: (2024)
por: Hasan, Mahamudul, et al.
Publicado: (2024)
Correcting Popularity Bias in Recommender Systems via Item Loss Equalization
por: Prent, Juno, et al.
Publicado: (2024)
por: Prent, Juno, et al.
Publicado: (2024)
Echoes in Filter Bubble: Diagnosing and Curing Popularity Bias in Generative Recommenders
por: Yin, Jun, et al.
Publicado: (2026)
por: Yin, Jun, et al.
Publicado: (2026)
On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective
por: Loveland, Donald, et al.
Publicado: (2025)
por: Loveland, Donald, et al.
Publicado: (2025)
Post-Training Denoising of User Profiles with LLMs in Collaborative Filtering Recommendation
por: Dervishaj, Ervin, et al.
Publicado: (2026)
por: Dervishaj, Ervin, et al.
Publicado: (2026)
Post-hoc Provider Fairness Adaptation via Hierarchical Exposure Alignment
por: Li, Jingzhi, et al.
Publicado: (2026)
por: Li, Jingzhi, et al.
Publicado: (2026)
Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias
por: Cai, Miaomiao, et al.
Publicado: (2024)
por: Cai, Miaomiao, et al.
Publicado: (2024)
Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias
por: Cai, Miaomiao, et al.
Publicado: (2025)
por: Cai, Miaomiao, et al.
Publicado: (2025)
Flow Matching for Collaborative Filtering
por: Liu, Chengkai, et al.
Publicado: (2025)
por: Liu, Chengkai, et al.
Publicado: (2025)
Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
por: Forster, Andrea, et al.
Publicado: (2025)
por: Forster, Andrea, et al.
Publicado: (2025)
Lightweight Embeddings for Graph Collaborative Filtering
por: Liang, Xurong, et al.
Publicado: (2024)
por: Liang, Xurong, et al.
Publicado: (2024)
Disentangled Contrastive Collaborative Filtering
por: Ren, Xubin, et al.
Publicado: (2023)
por: Ren, Xubin, et al.
Publicado: (2023)
Neural Causal Graph Collaborative Filtering
por: Wang, Xiangmeng, et al.
Publicado: (2023)
por: Wang, Xiangmeng, et al.
Publicado: (2023)
Representation Quantization for Collaborative Filtering Augmentation
por: Luo, Yunze, et al.
Publicado: (2025)
por: Luo, Yunze, et al.
Publicado: (2025)
General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
por: Zhang, An, et al.
Publicado: (2024)
por: Zhang, An, et al.
Publicado: (2024)
Intent Propagation Contrastive Collaborative Filtering
por: Li, Haojie, et al.
Publicado: (2026)
por: Li, Haojie, et al.
Publicado: (2026)
On Inherited Popularity Bias in Cold-Start Item Recommendation
por: Meehan, Gregor, et al.
Publicado: (2025)
por: Meehan, Gregor, et al.
Publicado: (2025)
The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias
por: Müllner, Peter, et al.
Publicado: (2024)
por: Müllner, Peter, et al.
Publicado: (2024)
Popular News Always Compete for the User's Attention! POPK: Mitigating Popularity Bias via a Temporal-Counterfactual
por: Azevedo, Igor L. R., et al.
Publicado: (2024)
por: Azevedo, Igor L. R., et al.
Publicado: (2024)
Understanding Embedding Scaling in Collaborative Filtering
por: He, Yicheng, et al.
Publicado: (2025)
por: He, Yicheng, et al.
Publicado: (2025)
Feedback Reciprocal Graph Collaborative Filtering
por: Chen, Weijun, et al.
Publicado: (2024)
por: Chen, Weijun, et al.
Publicado: (2024)
PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering
por: Qin, Yifang, et al.
Publicado: (2024)
por: Qin, Yifang, et al.
Publicado: (2024)
Bridging Semantic Understanding and Popularity Bias with LLMs
por: Luo, Renqiang, et al.
Publicado: (2026)
por: Luo, Renqiang, et al.
Publicado: (2026)
Investigating Popularity Bias Amplification in Recommender Systems Employed in the Entertainment Domain
por: Kowald, Dominik
Publicado: (2025)
por: Kowald, Dominik
Publicado: (2025)
Identifying and Upweighting Power-Niche Users to Mitigate Popularity Bias in Recommendations
por: Liu, David, et al.
Publicado: (2025)
por: Liu, David, et al.
Publicado: (2025)
Mitigating Popularity Bias in Counterfactual Explanations using Large Language Models
por: Hasami, Arjan, et al.
Publicado: (2025)
por: Hasami, Arjan, et al.
Publicado: (2025)
Opening the Black Box: Interpretable Remedies for Popularity Bias in Recommender Systems
por: Ahmadov, Parviz, et al.
Publicado: (2025)
por: Ahmadov, Parviz, et al.
Publicado: (2025)
Lightweight Embeddings with Graph Rewiring for Collaborative Filtering
por: Liang, Xurong, et al.
Publicado: (2025)
por: Liang, Xurong, et al.
Publicado: (2025)
CF4J: Collaborative Filtering for Java
por: Ortega, Fernando, et al.
Publicado: (2024)
por: Ortega, Fernando, et al.
Publicado: (2024)
Hierarchical Matrix Factorization for Interpretable Collaborative Filtering
por: Sugahara, Kai, et al.
Publicado: (2023)
por: Sugahara, Kai, et al.
Publicado: (2023)
Large Language Models Enhanced Collaborative Filtering
por: Sun, Zhongxiang, et al.
Publicado: (2024)
por: Sun, Zhongxiang, et al.
Publicado: (2024)
Adaptive Hardness Negative Sampling for Collaborative Filtering
por: Lai, Riwei, et al.
Publicado: (2024)
por: Lai, Riwei, et al.
Publicado: (2024)
Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation
por: Xu, Jinfeng, et al.
Publicado: (2024)
por: Xu, Jinfeng, et al.
Publicado: (2024)
S-Diff: An Anisotropic Diffusion Model for Collaborative Filtering in Spectral Domain
por: Xia, Rui, et al.
Publicado: (2024)
por: Xia, Rui, et al.
Publicado: (2024)
Cluster-based Graph Collaborative Filtering
por: Liu, Fan, et al.
Publicado: (2024)
por: Liu, Fan, et al.
Publicado: (2024)
Ejemplares similares
-
Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering
por: Islam, Md Aminul, et al.
Publicado: (2026) -
Correcting for Position Bias in Learning to Rank: A Control Function Approach
por: Islam, Md Aminul, et al.
Publicado: (2025) -
Prompt-Based LLMs for Position Bias-Aware Reranking in Personalized Recommendations
por: Islam, Md Aminul, et al.
Publicado: (2025) -
Rethinking Popularity Bias in Collaborative Filtering via Analytical Vector Decomposition
por: Liu, Lingfeng, et al.
Publicado: (2025) -
Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems
por: Huang, Jin, et al.
Publicado: (2024)