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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D2MoE dynamically allocates expert resources in graph MoEs via difficulty-driven top-p routing based on predictive entropy, yielding higher accuracy and lower memory/time costs on node classification benchmarks.
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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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Learning How Much to Think: Difficulty-Aware Dynamic MoEs for Graph Node Classification
D2MoE dynamically allocates expert resources in graph MoEs via difficulty-driven top-p routing based on predictive entropy, yielding higher accuracy and lower memory/time costs on node classification benchmarks.