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In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems.
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Session-based Recommendations with Recurrent Neural Networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk
Cited in the paper.
Attention Is All You Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin
Cited in the paper.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova
Cited in the paper.
Self-Attentive Sequential Recommendation
Wang-Cheng Kang and Julian McAuley
Cited in the paper.
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang
Cited in the paper.
S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization
Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen
Cited in the paper.
Contrastive Learning for Sequential Recommendation
Xu Xie, Fei Sun, Zhaoyang Liu, Shiwen Wu, Jinyang Gao, Bolin Ding, and Bin Cui
Cited in the paper.
Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
Fajie Yuan, Xiangnan He, Alexandros Karatzoglou, and Liguang Zhang
Cited in the paper.
UPRec: User-Aware Pre-training for Recommender Systems
Chaojun Xiao, Ruobing Xie, Yuan Yao, Zhiyuan Liu, Maosong Sun, Xu Zhang, and Leyu Lin
Cited in the paper.
Towards Universal Sequence Representation Learning for Recommender Systems
Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, and Ji-Rong Wen
Cited in the paper.
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, and Yongfeng Zhang
Cited in the paper.
M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems
Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang
Cited in the paper.
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