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Found 4 papers, 3 papers with code
LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking
Recently, large language models (LLMs) have exhibited significant progress in language understanding and generation.
Synthetic Data and Simulators for Recommendation Systems: Current State and Future Directions
Synthetic data and simulators have the potential to markedly improve the performance and robustness of recommendation systems.
CHAMELEON: A Deep Learning Meta-Architecture for News Recommender Systems [Phd. Thesis]
The main contribution of this research was named CHAMELEON, a Deep Learning meta-architecture designed to tackle the specific challenges of news recommendation.
Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks
The recommendation of news is often considered to be challenging, since the relevance of an article for a user can depend on a variety of factors, including the user's short-term reading interests, the reader's context, or the recency or popularity of an article.
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