MAIL constructs modality-aware ID-free identities via dynamic positional encoding modulation and applies counterfactual structure learning with popularity penalization, yielding 7.81% Recall@10 and 12.81% NDCG@10 gains on five Amazon datasets.
Vbpr: visual bayesian personalized ranking from implicit feedback
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Bi-NAS applies bi-level NAS to search explanation architectures and LLMs for text generation, reporting gains in both recommendation accuracy and explanation effectiveness across four real-world datasets.
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Modality-Aware Identity Construction and Counterfactual Structure Learning for ID-Free Multimodal Recommendation
MAIL constructs modality-aware ID-free identities via dynamic positional encoding modulation and applies counterfactual structure learning with popularity penalization, yielding 7.81% Recall@10 and 12.81% NDCG@10 gains on five Amazon datasets.
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Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search
Bi-NAS applies bi-level NAS to search explanation architectures and LLMs for text generation, reporting gains in both recommendation accuracy and explanation effectiveness across four real-world datasets.