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Transformers4NewsRec: A Transformer-based News Recommendation Framework

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arxiv 2410.13125 v1 pith:F5U56M4R submitted 2024-10-17 cs.IR

classification cs.IR
keywords modelsframeworknewstransformers4newsrecincludingrecommendationvariousallowing
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Pre-trained transformer models have shown great promise in various natural language processing tasks, including personalized news recommendations. To harness the power of these models, we introduce Transformers4NewsRec, a new Python framework built on the \textbf{Transformers} library. This framework is designed to unify and compare the performance of various news recommendation models, including deep neural networks and graph-based models. Transformers4NewsRec offers flexibility in terms of model selection, data preprocessing, and evaluation, allowing both quantitative and qualitative analysis.

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