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Found 4 papers, 3 papers with code
Formalizing Multimedia Recommendation through Multimodal Deep Learning
Recommender systems (RSs) offer personalized navigation experiences on online platforms, but recommendation remains a challenging task, particularly in specific scenarios and domains.
On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis
Multimodal-aware recommender systems (MRSs) exploit multimodal content (e. g., product images or descriptions) as items' side information to improve recommendation accuracy.
Counterfactual Reasoning for Bias Evaluation and Detection in a Fairness under Unawareness setting
Our experiments show that, even if the model is trained without sensitive features, it often suffers discriminatory biases.
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning
The increasing application of Artificial Intelligence and Machine Learning models poses potential risks of unfair behavior and, in light of recent regulations, has attracted the attention of the research community.
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