WPGRec is a new sequential recommender that performs multi-scale temporal modeling via stationary wavelet packets and injects high-order collaborative information through scale-aligned graph propagation with energy-aware gated fusion.
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4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
A two-phase data construction framework generates explanatory rationales from user feedback and applies uncertainty-based distillation to fine-tune lightweight LLMs as preference-aligned user simulators for recommender systems.
RCL adds similarity-based weak positive samples to supervised contrastive learning in sequential recommendation and reports an average 4.88% improvement over state-of-the-art methods across six datasets.
Empirical study of DAO forums finds frequent misalignment between token holders' stated priorities and delegate voting, worsened by ranking-based delegation interfaces.
citing papers explorer
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WPGRec: Wavelet Packet Guided Graph Enhanced Sequential Recommendation
WPGRec is a new sequential recommender that performs multi-scale temporal modeling via stationary wavelet packets and injects high-order collaborative information through scale-aligned graph propagation with energy-aware gated fusion.
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Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation
A two-phase data construction framework generates explanatory rationales from user feedback and applies uncertainty-based distillation to fine-tune lightweight LLMs as preference-aligned user simulators for recommender systems.
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Relative Contrastive Learning for Sequential Recommendation with Similarity-based Positive Pair Selection
RCL adds similarity-based weak positive samples to supervised contrastive learning in sequential recommendation and reports an average 4.88% improvement over state-of-the-art methods across six datasets.
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Fairness in Token Delegation: Mitigating Voting Power Concentration in DAOs
Empirical study of DAO forums finds frequent misalignment between token holders' stated priorities and delegate voting, worsened by ranking-based delegation interfaces.