NF-NPCDR enhances neural processes with normalizing flows to model personalized multi-interest preferences and uses a preference pool plus adaptive decoder to improve cross-domain recommendations for cold-start users.
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4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4verdicts
UNVERDICTED 4representative citing papers
A structure-aware RL fairness attack with joint item and gender selection policies is introduced and shown effective on four recommender models across two datasets.
RecFlash uses frequency-based data remapping in NAND flash in-storage computing to improve recommendation inference latency by up to 81% and energy consumption by 91.9% over prior ISC architectures.
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.
citing papers explorer
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Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
NF-NPCDR enhances neural processes with normalizing flows to model personalized multi-interest preferences and uses a preference pool plus adaptive decoder to improve cross-domain recommendations for cold-start users.
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Fairness Attacks on Recommender Systems
A structure-aware RL fairness attack with joint item and gender selection policies is introduced and shown effective on four recommender models across two datasets.
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RecFlash: Fast Recommendation System on In-Storage Computing with Frequency-Based Data Mapping
RecFlash uses frequency-based data remapping in NAND flash in-storage computing to improve recommendation inference latency by up to 81% and energy consumption by 91.9% over prior ISC architectures.
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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.