Papers by Andreea Iana

    2 papers
    Train Once, Use Flexibly: A Modular Framework for Multi-Aspect Neural News Recommendation (2024.findings-emnlp)

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    Challenge: Recent neural news recommenders (NNRs) extend content-based recommendation by aligning additional aspects between candidate news and user history or diversifying recommendations w.r.t. these aspects require retraining of the model with a modified objective.
    Approach: They introduce a modular framework for multi-aspect neural news recommendation that supports on-the-fly customization over individual aspects at inference time.
    Outcome: The proposed framework outperforms state-of-the-art NNRs on both content-based recommendation and single- and multi-aspect customization.
    NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation (2023.emnlp-demo)

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    Challenge: Existing open source repositories expose a multitude of programming languages, libraries, and implementation differences, hindering reproducibility and extensibility.
    Approach: NewsRecLib is an open-source library for training and evaluating neural news recommendation models.
    Outcome: The open-source library provides implementations of several prominent neural models, training methods, standard evaluation benchmarks, and evaluation metrics for news recommendation.

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