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This paper presents an open-source toolbox, MMRec for multimodal recommendation.
Multimodal machine learning: A survey and taxonomy
Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency. 2018 · 2018
Earlier work this paper cites.
Cornac: A Comparative Framework for Multimodal Recommender Systems
Aghiles Salah, Quoc-Tuan Truong, and Hady W Lauw. 2020 · 2020
Earlier work this paper cites.
Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Diffusion-Based Graph Contrastive Learning for Recommendation with Implicit Feedback. In International Conference on Database Systems for Advanced Applications . Springer, 232–247
Lingzi Zhang, Yong Liu, Xin Zhou, Chunyan Miao, Guoxin Wang, and Haihong Tang. 2022 · 2022
Earlier work this paper cites.
A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation
Xin Zhou. 2022 · 2022
Cited alongside, same era.
Capturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation
Jiazheng Jing, Yinan Zhang, Xin Zhou, and Zhiqi Shen. 2023 · 2023
Cited alongside, same era.
Hongyu Zhou, Xin Zhou, Zhiwei Zeng, Lingzi Zhang, and Zhiqi Shen. 2023d · 2023
Cited alongside, same era.
Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation
Hongyu Zhou, Xin Zhou, Lingzi Zhang, and Zhiqi Shen. 2023e · 2023
Cited alongside, same era.
Layer-refined graph convolutional networks for recommendation. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) . IEEE, 1247–1259
Xin Zhou, Donghui Lin, Yong Liu, and Chunyan Miao. 2023a · 2023
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Selfcf: A simple framework for self-supervised collaborative filtering
Xin Zhou, Aixin Sun, Yong Liu, Jie Zhang, and Chunyan Miao. 2023b · 2023
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Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You, and Feijun Jiang. 2023c · 2023
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