A unified, comprehensive and efficient recommendation library

Sequential model-based optimization with a `scipy.optimize` interface

GRID: Generative Recommendation with Semantic IDs

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

Recommender Systems Paperlist that I am interested in

Code for CIKM2020 "S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization"

Sequential deep matching model for recommender system at Alibaba

A highly-modularized and recommendation-efficient recommendation library based on PyTorch.

rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.

Must-read Papers for Recommender Systems (RS)

Code for TPAMI2025 paper "EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning"

Several sequential recommended models implemented by tenosrflow1.x

Generative model for sequential recommendation based on Convolution Neural Networks (CNN))

Code for CIKM2020 "S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization"

A box of core libraries for recommendation model development

Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".

KDD 2024 Best Student Paper | DR4SR: dataset regeneration for sequential recommendation.

[SIGIR'2024] "SelfGNN: Self-Supervised Graph Neural Networks for Sequential Recommendation"

The code for the paper "MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation" (ACM MM'23).