M <sup>3</sup> oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework-Reference-Cited by-同舟云学术

M ³ oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework

Published:2024-07-10 Issue: Volume:4 Page:893-902
ISSN:
Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zhang Zijian¹^ORCID,Liu Shuchang²^ORCID,Yu Jiaao²^ORCID,Cai Qingpeng²^ORCID,Zhao Xiangyu³^ORCID,Zhang Chunxu⁴^ORCID,Liu Ziru³^ORCID,Liu Qidong⁵^ORCID,Zhao Hongwei⁴^ORCID,Hu Lantao²^ORCID,Jiang Peng²^ORCID,Gai Kun⁶^ORCID

Affiliation:

1. Jilin University & City University of Hong Kong, Changchun, China

2. Kuaishou Technology, Beijing, China

3. City University of Hong Kong, Hong Kong, Hong Kong

4. Jilin University, Changchun, China

5. Xi'an Jiaotong University & City University of Hong Kong, Xi'an, China

6. Unaffiliated, Beijing, China

Funder

APRC - CityU New Research Initiatives

Kuaishou

Provincial Science and Technology Innovation Special Fund Project of Jilin Province

Fundamental Research Funds for the Central Universities, JLU

Hong Kong Environmental and Conservation Fund

Research Impact Fund

CityU - HKIDS Early Career Research Grant

Hong Kong ITC Innovation and Technology Fund Midstream Research Programme for Universities Project

SIRG - CityU Strategic Interdisciplinary Research Grant

Natural Science Foundation of Jilin Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657686

Reference38 articles.

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2. PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information

3. Multi-domain learning by confidence-weighted parameter combination

4. Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, and Ruiming Tang. 2023 a. Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation. arXiv preprint arXiv:2309.02061 (2023).

5. AutoTransfer: Instance Transfer for Cross-Domain Recommendations

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