Papers with Code 아카이브
Exposure Fairness
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits
Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance
Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems
Simultaneously Achieving Group Exposure Fairness and Within-Group Meritocracy in Stochastic Bandits
Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study
Fairness of Exposure in Dynamic Recommendation
FARA: Future-aware Ranking Algorithm for Fairness Optimization
Joint Multisided Exposure Fairness for Recommendation
FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback
Vertical Allocation-based Fair Exposure Amortizing in Ranking
Understanding and Mitigating Multi-Sided Exposure Bias in Recommender Systems
Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems
User-item matching for recommendation fairness
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.