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NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

Bridging LLM and Recommender System.

This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS)

fastFM: A Library for Factorization Machines

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.

HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training

A Comparative Framework for Multimodal Recommender Systems

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.