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Found 4 papers, 1 papers with code
GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation
The generated queries naturally serve as interpretable representations of user interests and can be searched to recommend cold-start items.
Contrastive Learning for Interactive Recommendation in Fashion
Recommender systems and search are both indispensable in facilitating personalization and ease of browsing in online fashion platforms.
OutfitTransformer: Learning Outfit Representations for Fashion Recommendation
For compatibility prediction, we design an outfit token to capture a global outfit representation and train the framework using a classification loss.
Semi-Supervised Learning with Auxiliary Evaluation Component for Large Scale e-Commerce Text Classification
To tackle this challenge, in this paper, we propose a semi-supervised learning method to utilize unlabeled data and user feedback signals to improve the performance of ML models.
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