arXiv:2503.23040
공식 코드 · Papers with Code
Reproducibility Companion Paper:In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems
원문 초록
In this paper, we reproduce experimental results presented in our earlier work titled "In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems" that was presented in the proceeding of the 31st ACM International Conference on Multimedia.This work aims to verify the effectiveness of our previously proposed method and provide guidance for reproducibility. We present detailed descriptions of our preprocessed datasets, the structure of our source code, configuration file settings, experimental environment, and the reproduced experimental results.
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A Reproducibility Study of Product-side Fairness in Bundle Recommendation
Addressing Correlated Latent Exogenous Variables in Debiased Recommender Systems
Looking for Fairness in Recommender Systems
Graph Learning
LumiCRS: Asymmetric Contrastive Prototype Learning for Long-Tail Conversational Movie Recommendation
BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization
토론
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