On the public citation graph

Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning

https://doi.org/10.1145/3664931
0 signed · 59 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-0-387-84808-2openalex-snapshot
Discrete Energy on Rectifiable Sets
inferredcites →https://doi.org/10.1007/978-3-030-30671-7_6openalex-snapshot
On Minimum Discrepancy Estimation for Deep Domain Adaptation
inferredcites →https://doi.org/10.1007/s11432-020-3404-yopenalex-snapshot
FairCF: fairness-aware collaborative filtering
inferredcites →https://doi.org/10.1007/s11704-021-0261-8openalex-snapshot
Graph convolution machine for context-aware recommender system
inferredcites →https://doi.org/10.1007/s11704-023-2655-2openalex-snapshot
How graph convolutions amplify popularity bias for recommendation?
inferredcites →https://doi.org/10.1016/0925-2312(93)90006-oopenalex-snapshot
Backpropagation and stochastic gradient descent method
inferredcites →https://doi.org/10.1098/rsif.2014.0378openalex-snapshot
The Matthew effect in empirical data
inferredcites →https://doi.org/10.1109/icdm.2002.1183878openalex-snapshot
Proceedings 2002 IEEE International Conference on Data Mining. ICDM 2002
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/tkde.2022.3145690openalex-snapshot
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
inferredcites →https://doi.org/10.1109/tkde.2022.3218994openalex-snapshot
Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation
inferredcites →https://doi.org/10.1109/tkde.2023.3282907openalex-snapshot
Self-Supervised Learning for Recommender Systems: A Survey
inferredcites →https://doi.org/10.1109/tkde.2023.3343402openalex-snapshot
Hyperbolic Graph Learning for Social Recommendation
inferredcites →https://doi.org/10.1109/tpami.2021.3068236openalex-snapshot
Progressive and Aligned Pose Attention Transfer for Person Image Generation
inferredcites →https://doi.org/10.1145/2396761.2398519openalex-snapshot
Discover breaking events with popular hashtags in twitter
inferredcites →https://doi.org/10.1145/2556195.2556248openalex-snapshot
Improving pairwise learning for item recommendation from implicit feedback
inferredcites →https://doi.org/10.1145/2827872openalex-snapshot
The MovieLens Datasets
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3077136.3080797openalex-snapshot
Attentive Collaborative Filtering
inferredcites →https://doi.org/10.1145/3240323.3240360openalex-snapshot
Causal embeddings for recommendation
inferredcites →https://doi.org/10.1145/3331184.3331192openalex-snapshot
An Efficient Adaptive Transfer Neural Network for Social-aware Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331267openalex-snapshot
Neural Graph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3397271.3401063openalex-snapshot
LightGCN
inferredcites →https://doi.org/10.1145/3404835openalex-snapshot
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
inferredcites →https://doi.org/10.1145/3404835.3462875openalex-snapshot
Causal Intervention for Leveraging Popularity Bias in Recommendation
inferredcites →https://doi.org/10.1145/3404835.3462919openalex-snapshot
AutoDebias: Learning to Debias for Recommendation
inferredcites →https://doi.org/10.1145/3437963.3441820openalex-snapshot
Popularity-Opportunity Bias in Collaborative Filtering
inferredcites →https://doi.org/10.1145/3447548.3467249openalex-snapshot
Deconfounded Recommendation for Alleviating Bias Amplification
inferredcites →https://doi.org/10.1145/3477495.3531937openalex-snapshot
Are Graph Augmentations Necessary?
inferredcites →https://doi.org/10.1145/3477495.3531959openalex-snapshot
CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems
inferredcites →https://doi.org/10.1145/3477495.3532005openalex-snapshot
Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering
inferredcites →https://doi.org/10.1145/3523227.3546757openalex-snapshot
Countering Popularity Bias by Regularizing Score Differences
inferredcites →https://doi.org/10.1145/3534678.3539253openalex-snapshot
Towards Representation Alignment and Uniformity in Collaborative Filtering
inferredcites →https://doi.org/10.1145/3534678.3539297openalex-snapshot
Semi-supervised Drifted Stream Learning with Short Lookback
inferredcites →https://doi.org/10.1145/3539618.3591691openalex-snapshot
Generative-Contrastive Graph Learning for Recommendation
inferredcites →https://doi.org/10.1145/3547333openalex-snapshot
A Survey on the Fairness of Recommender Systems
inferredcites →https://doi.org/10.1145/3564284openalex-snapshot
Bias and Debias in Recommender System: A Survey and Future Directions
inferredcites →https://doi.org/10.1145/3579163openalex-snapshot
Malayalam Natural Language Processing: Challenges in Building a Phrase-Based Statistical Machine Translation System
inferredcites →https://doi.org/10.1145/3582002openalex-snapshot
Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset
inferredcites →https://doi.org/10.1145/3583780.3615492openalex-snapshot
Popularity-aware Distributionally Robust Optimization for Recommendation System
inferredcites →https://doi.org/10.1145/3594871openalex-snapshot
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System
inferredcites →https://doi.org/10.1214/aoms/1177729392openalex-snapshot
Stochastic Estimation of the Maximum of a Regression Function
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015989openalex-snapshot
Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources
inferredcites →https://doi.org/10.1609/aaai.v34i01.5330openalex-snapshot
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
inferredcites →https://doi.org/10.1609/aaai.v37i4.25617openalex-snapshot
Fair Representation Learning for Recommendation: A Mutual Information Perspective
inferredcites →https://doi.org/10.5555/2188385.2188410openalex-snapshot
A kernel two-sample test

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s10044-025-01494-xopenalex-snapshot
Contour-Aware contrastive learning for 3D knee segmentation from MR images
inferred← citeshttps://doi.org/10.1007/s11704-025-40591-2openalex-snapshot
Breaking student-concept sparsity barrier for cognitive diagnosis
inferred← citeshttps://doi.org/10.1007/s43926-026-00434-3openalex-snapshot
Evaluation and success rate prediction of innovation and entrepreneurship projects using a group recommendation algorithm
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.129427openalex-snapshot
Wasserstein distance-based graph contrastive learning for recommendation
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114345openalex-snapshot
Multi-Cause Deconfounding for Recommender Systems with Latent Confounders
inferred← citeshttps://doi.org/10.1016/j.neunet.2025.107977openalex-snapshot
Learning instrumental variable representation for debiasing in recommender systems
inferred← citeshttps://doi.org/10.1109/icvadv63329.2025.10961865openalex-snapshot
Hybrid Recommender Systems: Bridging Accuracy Gaps with Quantitative Evidence
inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11227217openalex-snapshot
Building a Chinese Medical Dialogue System: Integrating Large-scale Corpora and Novel Models
inferred← citeshttps://doi.org/10.1109/tkde.2024.3511602openalex-snapshot
Making Non-Overlapping Matters: An Unsupervised Alignment Enhanced Cross-Domain Cold-Start Recommendation
inferred← citeshttps://doi.org/10.1109/tkde.2025.3638343openalex-snapshot
Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias
inferred← citeshttps://doi.org/10.1145/3705328.3748035openalex-snapshot
On Inherited Popularity Bias in Cold-Start Item Recommendation
inferred← citeshttps://doi.org/10.1145/3757925openalex-snapshot
LLM-Enhanced User–Item Interactions: Leveraging Edge Information for Optimized Recommendations
inferred← citeshttps://doi.org/10.1145/3770855.3817818openalex-snapshot
ReAU: A Global-to-Local Perspective for Refining Alignment and Uniformity in Collaborative Filtering
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.