[18] David Ben-Shimon, Alexander Tsikinovsky, Michael Friedmann, Bracha Shapira, Lior Rokach, and Johannes Hoerle. Recsys challenge 2015 and the yoochoose dataset. In Proceedings of the 9th ACM Conference on Recommender Systems, pages 357-358, 2015.
[19] Dressipi dataset (http://www.recsyschallenge.com/2022), 2022.
[20] Shiwen Wu, Fei Sun, Wentao Zhang, Xu Xie, and Bin Cui. Graph neural networks in recommender systems: a survey. ACM Computing Surveys, 55(5):1-37, 2022.
[21] Tianchi. Ijcai-15 repeat buyers prediction dataset, 2018.
[22] Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, and Xia Hu. Harnessing the power of llms in practice: A survey on chatgpt and beyond. arXiv preprint arXiv:2304.13712, 2023.
[23] Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. A survey of large language models. arXiv preprint arXiv:2303.18223, 2023.
[24] Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, et al. A comprehensive survey on pretrained foundation models: A history from bert to chatgpt. arXiv preprint arXiv:2302.09419, 2023.
[25] Diginetica dataset (https://competitions.codalab.org/competitions/11161), 2016.
[26] Hongzhi Yin, Bin Cui, Jing Li, Junjie Yao, and Chen Chen. Challenging the long tail recommendation. arXiv preprint arXiv:1205.6700, 2012.
[27] Siyi Liu and Yujia Zheng. Long-tail session-based recommendation. In Proceedings of the 14th ACM Conference on Recommender Systems, pages 509-514, 2020.
[28] Chen Gao, Xiangning Chen, Fuli Feng, Kai Zhao, Xiangnan He, Yong Li, and Depeng Jin. Cross-domain recommendation without sharing user-relevant data. In The world wide web conference, pages 491-502, 2019.
[29] Antoine Nzeyimana and Andre Niyongabo Rubungo. Kinyabert: a morphology-aware kinyarwanda language model. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5347-5363, 2022.
[30] Phillip Rust, Jonas Pfeiffer, Ivan Vulic, Sebastian Ruder, and Iryna Gurevych. How good is your tokenizer? on the monolingual performance of multilingual language models. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 3118-3135, 2021.
[31] Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, et al. Choosing transfer languages for cross-lingual learning. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3125–3135, 2019.
[32] Ashton Anderson, Ravi Kumar, Andrew Tomkins, and Sergei Vassilvitskii. The dynamics of repeat consumption. In Proceedings of the 23rd international conference on World wide web, pages 419-430, 2014.
[33] Jun Chen, Chaokun Wang, and Jianmin Wang. Will you "reconsume" the near past? fast prediction on short-term consumption behaviors. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 29, 2015.
[34] Austin R Benson, Ravi Kumar, and Andrew Tomkins. Modeling user consumption sequences. In Proceedings of the 25th International Conference on World Wide Web, pages 519-529, 2016.
[35] Pengjie Ren, Zhumin Chen, Jing Li, Zhaochun Ren, Jun Ma, and Maarten De Rijke. Repeat-net: A repeat aware neural recommendation machine for session-based recommendation. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 33, pages 4806-4813, 2019.
[36] Zhiqiang Pan, Fei Cai, Wanyu Chen, and Honghui Chen. Graph co-attentive session-based recommendation. ACM Transactions on Information Systems (TOIS), 40(4):1-31, 2021.
[37] Yujia Zheng, Siyi Liu, and Zailei Zhou. Balancing multi-level interactions for session-based recommendation. arXiv preprint arXiv:1910.13527, 2019.