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arXiv · 2310.01146

NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation

Andreea Iana·Goran Glavaš·Heiko Paulheim
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Abstract

NewsRecLib is an open-source library based on Pytorch-Lightning and Hydra developed for training and evaluating neural news recommendation models. The foremost goals of NewsRecLib are to promote reproducible research and rigorous experimental evaluation by (i) providing a unified and highly configurable framework for exhaustive experimental studies and (ii) enabling a thorough analysis of the performance contribution of different model architecture components and training regimes. NewsRecLib is highly modular, allows specifying experiments in a single configuration file, and includes extensive logging facilities. Moreover, NewsRecLib provides out-of-the-box implementations of several prominent neural models, training methods, standard evaluation benchmarks, and evaluation metrics for news recommendation.

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BibTeXRIS

Andreea Iana, Goran Glavaš, Heiko Paulheim. 2023-10-02. NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation. https://arxiv.org/abs/2310.01146

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