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Found 4 papers, 3 papers with code
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study
Large Multimodal Models (LMMs) have demonstrated impressive performance across various vision and language tasks, yet their potential applications in recommendation tasks with visual assistance remain unexplored.
Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems
To address these issues, we propose the REMI framework, consisting of an Interest-aware Hard Negative mining strategy (IHN) and a Routing Regularization (RR) method.
Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network
Based on this observation, we intuitively propose to remove the GNN propagation part, while the readout module will take on more responsibility in the model reasoning process.
Improving Sequential Recommendations via Bidirectional Temporal Data Augmentation with Pre-training
Our approach leverages bidirectional temporal augmentation and knowledge-enhanced fine-tuning to synthesize authentic pseudo-prior items that \emph{retain user preferences and capture deeper item semantic correlations}, thus boosting the model's expressive power.
