Awesome
Awesome-Generative-RecSys
A curated list of awesome Generative Recommender Systems - by Jihoo Kim
Research
Title | PublishedAt | Paper | Code | |
---|---|---|---|---|
1 | GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation | Preprint'23 | arXiv | |
2 | Generative Recommendation: Towards Next-generation Recommender Paradigm | Preprint'23 | arXiv | Github |
3 | DiffuRec: A Diffusion Model for Sequential Recommendation | Preprint'23 | arXiv | |
4 | Sequential Recommendation with Diffusion Models | Preprint'23 | arXiv | |
5 | Creating Synthetic Datasets for Collaborative Filtering Recommender Systems using Generative Adversarial Networks | Preprint'23 | arXiv | |
6 | Recommender Systems with Generative Retrieval | Preprint'23 | ||
7 | Diffusion Recommender Model | SIGIR'23 | arXiv | Github |
8 | Blurring-Sharpening Process Models for Collaborative Filtering | SIGIR'23 | arXiv | Github |
9 | IDNP: Interest Dynamics Modeling Using Generative Neural Processes for Sequential Recommendation | WSDM'23 | arXiv | |
10 | Generative Slate Recommendation with Reinforcement Learning | WSDM'23 | arXiv | Github |
11 | Generative Session-based Recommendation | WWW'22 | dl.acm | |
12 | Generative Adversarial Zero-Shot Learning for Cold-Start News Recommendation | CIKM'22 | dl.acm | |
13 | VAE-IPS: A Deep Generative Recommendation Method for Unbiased Learning from Implicit Feedback | RecSys'22 | ||
14 | From Abstract to Details: A Generative Multimodal Fusion Framework for Recommendation | MM'22 | dl.acm | |
15 | Privacy-Preserving Synthetic Data Generation for Recommendation Systems | SIGIR'22 | arXiv | Github |
16 | Generative Adversarial Framework for Cold-Start Item Recommendation | SIGIR'22 | dl.acm | Github |
17 | M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems | Preprint'22 | arXiv | |
18 | PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network | KDD'21 | ||
19 | PRGAN: Personalized Recommendation with Conditional Generative Adversarial Networks | ICDM'21 | ieee | |
20 | Generative Inverse Deep Reinforcement Learning for Online Recommendation | CIKM'21 | arXiv | |
21 | Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems | RecSys'21 | arXiv | Github |
22 | What Users Want? WARHOL: A Generative Model for Recommendation | RecSys'21 | arXiv | |
23 | Variation Control and Evaluation for Generative Slate Recommendations | WWW'21 | arXiv | Github |
24 | Learning to Recommend from Sparse Data via Generative User Feedback Authors | AAAI'21 | arXiv | |
25 | Interpretable Deep Generative Recommendation Models | JMLR'21 | ||
26 | GRN: Generative Rerank Network for Context-wise Recommendation | Preprint'21 | arXiv | |
27 | Sampling-Decomposable Generative Adversarial Recommender | NeurIPS'20 | arXiv | |
28 | Exploring Missing Interactions: A Convolutional Generative Adversarial Network for Collaborative Filtering | CIKM'20 | dl.acm | |
29 | Deep Global and Local Generative Model for Recommendation | WWW'20 | dl.acm | |
30 | AR-CF: Augmenting Virtual Users and Items in Collaborative Filtering for Addressing Cold-Start Problems | SIGIR'20 | ||
31 | Rating Augmentation with Generative Adversarial Networks towards Accurate Collaborative Filtering | WWW'19 | dl.acm | |
32 | CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped users | WWW'19 | arXiv | |
33 | A Simple Convolutional Generative Network for Next Item Recommendation | WSDM'19 | arXiv | |
34 | Generating Reliable Friends via Adversarial Training to Improve Social Recommendation | ICDM'19 | arXiv | Github |
35 | Generative Adversarial User Model for Reinforcement Learning Based Recommendation System | ICML'19 | Github | |
36 | Enhancing Collaborative Filtering with Generative Augmentation | KDD'19 | dl.acm | |
37 | A Deep Generative Approach to Search Extrapolation and Recommendation | KDD'19 | Github | |
38 | A Generative Model for Review-Based Recommendations | RecSys'19 | dl.acm | |
39 | Deep Generative Ranking for Personalized Recommendation | RecSys'19 | dl.acm | |
40 | RecGAN: Recurrent Generative Adversarial Networks for Recommendation Systems | RecSys'18 | ||
41 | CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks | CIKM'18 | dl.acm | |
42 | Compatibility Family Learning for Item Recommendation and Generation | AAAI'18 | arXiv | |
43 | GraphGAN: Graph Representation Learning with Generative Adversarial Nets | AAAI'18 | arXiv | Github |
44 | IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models | SIGIR'17 | arXiv | Github |
45 | Mobi-SAGE: A Sparse Additive Generative Model for Mobile App Recommendation | ICDE'17 | ieee | |
46 | Visually-Aware Fashion Recommendation and Design with Generative Image Models | ICDM'17 | arXiv | Github |
47 | Tag2Word: Using Tags to Generate Words for Content Based Tag Recommendation | CIKM'16 | dl.acm | |
48 | Multi-Word Generative Query Recommendation Using Topic Modeling | RecSys'16 | dl.acm | |
49 | Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation | KDD'15 | arXiv | |
50 | COM: a Generative Model for Group Recommendation | KDD'14 | dl.acm | |
51 | Exploring Social Influence for Recommendation - A Generative Model Approach | SIGIR'12 | arXiv |