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        <title>NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation</title>
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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.</abstract>
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    <identifier type="doi">10.18653/v1/2023.emnlp-demo.26</identifier>
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%0 Conference Proceedings
%T NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation
%A Iana, Andreea
%A Glavaš, Goran
%A Paulheim, Heiko
%Y Feng, Yansong
%Y Lefever, Els
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F iana-etal-2023-newsreclib
%X 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.
%R 10.18653/v1/2023.emnlp-demo.26
%U https://aclanthology.org/2023.emnlp-demo.26
%U https://doi.org/10.18653/v1/2023.emnlp-demo.26
%P 296-310

Markdown (Informal)

[NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation](https://aclanthology.org/2023.emnlp-demo.26) (Iana et al., EMNLP 2023)

• NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation (Iana et al., EMNLP 2023)

ACL

• Andreea Iana, Goran Glavaš, and Heiko Paulheim. 2023. NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 296–310, Singapore. Association for Computational Linguistics.