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Can Large Language Models Assess Serendipity in Recommender Systems?
In this investigation, a binary classification task was given to the LLMs to predict whether a user would find the recommended item serendipitously.
A Completely Locale-independent Session-based Recommender System by Leveraging Trained Model
In this paper, we propose a solution that won the 10th prize in the KDD Cup 2023 Challenge Task 2 (Next Product Recommendation for Underrepresented Languages/Locales).
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