Jianxin Ma
3 papers in the PaperMetrix corpus
Papers by this author
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Disentangled Self-Supervision in Sequential Recommenders
2020
To learn a sequential recommender, the existing methods typically adopt the sequence-to-item (seq2item) training strategy, which supervises a sequence model with a user's next behavior as the label and the user's past behaviors as the …
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M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems
2022 · arXiv (Cornell University)
Industrial recommender systems have been growing increasingly complex, may involve \emph{diverse domains} such as e-commerce products and user-generated contents, and can comprise \emph{a myriad of tasks} such as retrieval, ranking, explanation generation, and even AI-assisted …
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Learning Disentangled Representations for Recommendation
2019 · arXiv (Cornell University)
User behavior data in recommender systems are driven by the complex interactions of many latent factors behind the users' decision making processes. The factors are highly entangled, and may range from high-level ones that govern …