NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation
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.
Code (1)
Tasks
BenchmarkingNews RecommendationRecommendation SystemsMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
PyTorchVideo: A Deep Learning Library for Video Understanding
We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tasks, including classification, detection,…
Deep LearningSelf-Supervised LearningVideo UnderstandingPyTorch Tabular: A Framework for Deep Learning with Tabular Data
In spite of showing unreasonable effectiveness in modalities like Text and Image, Deep Learning has always lagged Gradient Boosting in tabular data - both in popularity and performance. But recently there have been newer…
Deep LearningSolo-learn: A Library of Self-supervised Methods for Visual Representation Learning
This paper presents solo-learn, a library of self-supervised methods for visual representation learning. Implemented in Python, using Pytorch and Pytorch lightning, the library fits both research and industry needs by fe…
Linear evaluationRepresentation LearningSelf-Supervised LearningFasterAI: A Lightweight Library for Creating Sparse Neural Networks
FasterAI is a PyTorch-based library, aiming to facilitate the utilization of deep neural networks compression techniques such as sparsification, pruning, knowledge distillation, or regularization. The library is built wi…
Knowledge DistillationNewsTorch: A PyTorch-based Toolkit for Learner-oriented News Recommendation
News recommender systems are devised to alleviate the information overload, attracting more and more researchers' attention in recent years. The lack of a dedicated learner-oriented news recommendation toolkit hinders th…