In comparing our proposed TALL with MultVAE, we noticed substantial enhancements in user utilities across all five subgroups, clearly demonstrating TALL's superior debiasing capabilities.
The results indicate that while WL provides some alleviation of mainstream bias, TALL consistently produced higher NDCG@20 scores across all subgroups, confirming its efficacy.
Direct comparisons with local learning methods, such as LOCA and EnLFT, reveal that TALL surpasses these models in effectiveness, particularly for niche users.
Overall, TALL not only addresses bias effectively but also significantly boosts the utility metrics for users categorized as having lower mainstream levels, marking a key innovation.
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