EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration-Reference-Cited by-同舟云学术

EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration

Published:2024-08-24 Issue: Volume:35 Page:3245-3254
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Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Wang Ye¹^ORCID,Xun Jiahao¹^ORCID,Hong Minjie²^ORCID,Zhu Jieming³^ORCID,Jin Tao²^ORCID,Lin Wang¹^ORCID,Li Haoyuan¹^ORCID,Li Linjun¹^ORCID,Xia Yan¹^ORCID,Zhao Zhou¹^ORCID,Dong Zhenhua³^ORCID

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Zhejiang University, Hangzhou, Zhejiang, China

3. Huawei Noah's Ark Lab, Shenzhen, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671775

Reference42 articles.

1. Autoregressive search engines: Generating substrings as document identifiers;Bevilacqua Michele;Advances in Neural Information Processing Systems,2022

2. Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597--1607.

3. Exploring Simple Siamese Representation Learning

4. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).

5. Zhenhua Dong, Jieming Zhu, Weiwen Liu, and Ruiming Tang. 2023. Ten Challenges in Industrial Recommender Systems. CoRR, Vol. abs/2310.04804 (2023).

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