A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations
Measuring Bias in Multimodal Models: Multimodal Composite Association Score
Evaluating Fairness Metrics
Utilizing Implicit Feedback for User Mainstreaminess Evaluation and Bias Detection in Recommender Systems
Preserving Utility in Fair Top-k Ranking with Intersectional Bias
Mitigating Position Bias in Hotels Recommender Systems
Improving Recommender System Diversity with Variational Autoencoders
Addressing Biases in the Texts using an End-to-End Pipeline Approach
Bootless Application of Greedy Re-ranking Algorithms in Fair Neural Team Formation
How do you feel? Information Retrieval in Psychotherapy and Fair Ranking Assessment
Understanding Search Behavior Bias in Wikipedia
Do you MIND? Reflections on the MIND dataset for research on diversity in news recommendations
Detecting and Measuring Social Bias of Arabic Generative Models in the Context of Search and Recommendation
What are we missing in algorithmic fairness? Discussing open challenges for fairness analysis in user profiling with Graph Neural Networks.