{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:08:38Z","timestamp":1765544918684,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,11,25]],"date-time":"2023-11-25T00:00:00Z","timestamp":1700870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,11,27]]},"DOI":"10.1145\/3604237.3626850","type":"proceedings-article","created":{"date-parts":[[2023,11,25]],"date-time":"2023-11-25T18:09:47Z","timestamp":1700935787000},"page":"141-149","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3102-9837","authenticated-orcid":false,"given":"Piotr","family":"Skalski","sequence":"first","affiliation":[{"name":"Innovation Lab, Featurespace, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6739-5689","authenticated-orcid":false,"given":"David","family":"Sutton","sequence":"additional","affiliation":[{"name":"Innovation Lab, Featurespace, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6333-1750","authenticated-orcid":false,"given":"Stuart","family":"Burrell","sequence":"additional","affiliation":[{"name":"Innovation Lab, Featurespace, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9400-4229","authenticated-orcid":false,"given":"Iker","family":"Perez","sequence":"additional","affiliation":[{"name":"Innovation Lab, Featurespace, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7727-1341","authenticated-orcid":false,"given":"Jason","family":"Wong","sequence":"additional","affiliation":[{"name":"Innovation Lab, Featurespace, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,11,25]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Arik and Tomas Pfister","author":"O.","year":"2020","unstructured":"Sercan\u00a0O. Arik and Tomas Pfister. 2020. TabNet: Attentive Interpretable Tabular Learning. arxiv:1908.07442https:\/\/arxiv.org\/abs\/1908.07442"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3526129"},{"volume-title":"Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.). Vol.\u00a033. Curran Associates","author":"Baevski Alexei","key":"e_1_3_2_1_3_1","unstructured":"Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations. In Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.). Vol.\u00a033. Curran Associates, Inc., 12449\u201312460."},{"key":"e_1_3_2_1_4_1","volume-title":"Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.). Vol.\u00a033. Curran Associates","author":"Tom Brown\u00a0et","year":"1877","unstructured":"Tom Brown\u00a0et al.2020. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.). Vol.\u00a033. Curran Associates, Inc., 1877\u20131901. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2020\/file\/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf"},{"key":"e_1_3_2_1_5_1","unstructured":"C.\u00a0Bayan Bruss Anish Khazane Jonathan Rider Richard Serpe Antonia Gogoglou and Keegan\u00a0E. Hines. 2019. DeepTrax: Embedding Graphs of Financial Transactions. arxiv:1907.07225\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/1907.07225"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3533271.3561727"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/3495724.3496555"},{"key":"e_1_3_2_1_8_1","unstructured":"Ting Chen Simon Kornblith Mohammad Norouzi and Geoffrey Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. arxiv:2002.05709https:\/\/arxiv.org\/abs\/2002.05709"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"e_1_3_2_1_11_1","volume-title":"International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=r1xMH1BtvB","author":"Clark Kevin","year":"2020","unstructured":"Kevin Clark, Minh-Thang Luong, Quoc\u00a0V. Le, and Christopher\u00a0D. Manning. 2020. ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=r1xMH1BtvB"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Alexis Conneau Alexei Baevski Ronan Collobert Abdelrahman Mohamed and Michael Auli. 2020. Unsupervised Cross-lingual Representation Learning for Speech Recognition. arxiv:2006.13979https:\/\/arxiv.org\/abs\/2006.13979","DOI":"10.21437\/Interspeech.2021-329"},{"key":"e_1_3_2_1_13_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arxiv:1810.04805https:\/\/arxiv.org\/abs\/1810.04805","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arxiv:1810.04805https:\/\/arxiv.org\/abs\/1810.04805"},{"key":"e_1_3_2_1_14_1","unstructured":"International\u00a0Organization for Standardization. [n. d.]. ISO 8583-1:2003 Financial transaction card originated messages \u2013 Interchange message specifications \u2013 Part 1: Messages data elements and code values. https:\/\/www.iso.org\/standard\/31628.html"},{"key":"e_1_3_2_1_15_1","unstructured":"Tianyu Gao Xingcheng Yao and Danqi Chen. 2021. SimCSE: Simple Contrastive Learning of Sentence Embeddings. In Empirical Methods in Natural Language Processing (EMNLP). https:\/\/arxiv.org\/abs\/2104.08821"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Antonia Gogoglou Brian Nguyen Alan Salimov Jonathan Rider and C.\u00a0Bayan Bruss. 2020. Navigating the Dynamics of Financial Embeddings over Time. arxiv:2007.00591https:\/\/arxiv.org\/abs\/2007.00591","DOI":"10.1145\/3383455.3422552"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86383-8_2"},{"key":"e_1_3_2_1_18_1","volume-title":"Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.). Vol.\u00a033. Curran Associates","author":"Jean-Bastien","year":"2020","unstructured":"Jean-Bastien Grill\u00a0et al.2020. Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning. In Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.). Vol.\u00a033. Curran Associates, Inc., 21271\u201321284. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2020\/file\/f3ada80d5c4ee70142b17b8192b2958e-Paper.pdf"},{"key":"e_1_3_2_1_19_1","volume-title":"Advances in Neural Information Processing Systems, I.\u00a0Guyon, U.\u00a0Von Luxburg, S.\u00a0Bengio, H.\u00a0Wallach, R.\u00a0Fergus, S.\u00a0Vishwanathan, and R.\u00a0Garnett (Eds.). Vol.\u00a030. Curran Associates","author":"Hamilton Will","year":"2017","unstructured":"Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive Representation Learning on Large Graphs. In Advances in Neural Information Processing Systems, I.\u00a0Guyon, U.\u00a0Von Luxburg, S.\u00a0Bengio, H.\u00a0Wallach, R.\u00a0Fergus, S.\u00a0Vishwanathan, and R.\u00a0Garnett (Eds.). Vol.\u00a030. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2017\/file\/5dd9db5e033da9c6fb5ba83c7a7ebea9-Paper.pdf"},{"key":"e_1_3_2_1_20_1","unstructured":"Xin Huang Ashish Khetan Milan Cvitkovic and Zohar Karnin. 2020. TabTransformer: Tabular Data Modeling Using Contextual Embeddings. arxiv:2012.06678https:\/\/arxiv.org\/abs\/2012.06678"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.05.018"},{"key":"e_1_3_2_1_22_1","volume-title":"ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=H1eA7AEtvS","author":"Lan Zhenzhong","year":"2020","unstructured":"Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=H1eA7AEtvS"},{"volume-title":"Complex Networks & Their Applications V","author":"Lebichot Bertrand","key":"e_1_3_2_1_23_1","unstructured":"Bertrand Lebichot, Fabian Braun, Olivier Caelen, and Marco Saerens. 2017. A graph-based, semi-supervised, credit card fraud detection system. In Complex Networks & Their Applications V, Hocine Cherifi, Sabrina Gaito, Walter Quattrociocchi, and Alessandra Sala (Eds.). Springer International Publishing, Cham, 721\u2013733."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3487553.3524643"},{"volume-title":"Graph Analytics for Real-Time Scoring of Cross-Channel Transactional Fraud","author":"Molloy Ian","key":"e_1_3_2_1_25_1","unstructured":"Ian Molloy, Suresh Chari, Ulrich Finkler, Mark Wiggerman, Coen Jonker, Ted Habeck, Youngja Park, Frank Jordens, and Ron van Schaik. 2017. Graph Analytics for Real-Time Scoring of Cross-Channel Transactional Fraud. In Financial Cryptography and Data Security, Jens Grossklags and Bart Preneel (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 22\u201340."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","unstructured":"Deepak Pathak Philipp Kr\u00e4henb\u00fchl Jeff Donahue Trevor Darrell and Alexei Efros. [n. d.]. Context Encoders: Feature Learning by Inpainting. In Computer Vision and Pattern Recognition (CVPR). https:\/\/doi.org\/10.1109\/CVPR.2016.278","DOI":"10.1109\/CVPR.2016.278"},{"key":"e_1_3_2_1_27_1","unstructured":"Alec Radford and Ilya Sutskever. 2018. Improving Language Understanding by Generative Pre-Training. In arxiv. https:\/\/cdn.openai.com\/research-covers\/language-unsupervised\/language_understanding_paper.pdf"},{"key":"e_1_3_2_1_28_1","unstructured":"Alec Radford Jeff Wu Rewon Child David Luan Dario Amodei and Ilya Sutskever. 2019. Language Models are Unsupervised Multitask Learners. (2019). https:\/\/d4mucfpksywv.cloudfront.net\/better-language-models\/language-models.pdf"},{"key":"e_1_3_2_1_29_1","volume-title":"SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training. https:\/\/openreview.net\/forum?id=nL2lDlsrZU","author":"Somepalli Gowthami","year":"2022","unstructured":"Gowthami Somepalli, Avi Schwarzschild, Micah Goldblum, C.\u00a0Bayan Bruss, and Tom Goldstein. 2022. SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training. https:\/\/openreview.net\/forum?id=nL2lDlsrZU"},{"key":"e_1_3_2_1_30_1","volume-title":"Selfie: Self-supervised Pretraining for Image Embedding. arxiv:1906.02940https:\/\/arxiv.org\/abs\/1906.02940","author":"Trinh H.","year":"2019","unstructured":"Trieu\u00a0H. Trinh, Minh-Thang Luong, and Quoc\u00a0V. Le. 2019. Selfie: Self-supervised Pretraining for Image Embedding. arxiv:1906.02940https:\/\/arxiv.org\/abs\/1906.02940"},{"key":"e_1_3_2_1_31_1","volume-title":"Advances in Neural Information Processing Systems, M.\u00a0Ranzato, A.\u00a0Beygelzimer, Y.\u00a0Dauphin, P.S. Liang, and J.\u00a0Wortman Vaughan (Eds.). Vol.\u00a034. Curran Associates","author":"Ucar Talip","year":"1885","unstructured":"Talip Ucar, Ehsan Hajiramezanali, and Lindsay Edwards. 2021. SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. In Advances in Neural Information Processing Systems, M.\u00a0Ranzato, A.\u00a0Beygelzimer, Y.\u00a0Dauphin, P.S. Liang, and J.\u00a0Wortman Vaughan (Eds.). Vol.\u00a034. Curran Associates, Inc., 18853\u201318865."},{"volume-title":"Mining Data for Financial Applications, Valerio Bitetta, Ilaria Bordino","author":"Van\u00a0Belle Rafa\u00ebl","key":"e_1_3_2_1_32_1","unstructured":"Rafa\u00ebl Van\u00a0Belle, Sandra Mitrovi\u0107, and Jochen De\u00a0Weerdt. 2020. Representation Learning in Graphs for Credit Card Fraud Detection. In Mining Data for Financial Applications, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Stefano Pascolutti, and Giovanni Ponti (Eds.). Springer International Publishing, Cham, 32\u201346."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116463"},{"key":"e_1_3_2_1_34_1","unstructured":"Aaron van\u00a0den Oord Yazhe Li and Oriol Vinyals. 2019. Representation Learning with Contrastive Predictive Coding. arxiv:1807.03748https:\/\/arxiv.org\/abs\/1807.03748"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings of the 38th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0139)","author":"Zbontar Jure","year":"2021","unstructured":"Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stephane Deny. 2021. Barlow Twins: Self-Supervised Learning via Redundancy Reduction. In Proceedings of the 38th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0139), Marina Meila and Tong Zhang (Eds.). PMLR, 12310\u201312320. https:\/\/proceedings.mlr.press\/v139\/zbontar21a.html"},{"key":"e_1_3_2_1_37_1","volume-title":"International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=r1Ddp1-Rb","author":"Zhang Hongyi","year":"2018","unstructured":"Hongyi Zhang, Moustapha Cisse, Yann\u00a0N. Dauphin, and David Lopez-Paz. 2018. mixup: Beyond Empirical Risk Minimization. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=r1Ddp1-Rb"},{"key":"e_1_3_2_1_38_1","unstructured":"Jiachen Zhu Rafael\u00a0M. Moraes Serkan Karakulak Vlad Sobol Alfredo Canziani and Yann LeCun. 2022. TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning. arxiv:2206.10698\u00a0[cs.CV]"}],"event":{"name":"ICAIF '23: 4th ACM International Conference on AI in Finance","acronym":"ICAIF '23","location":"Brooklyn NY USA"},"container-title":["4th ACM International Conference on AI in Finance"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3604237.3626850","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3604237.3626850","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:35:59Z","timestamp":1755884159000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3604237.3626850"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,25]]},"references-count":38,"alternative-id":["10.1145\/3604237.3626850","10.1145\/3604237"],"URL":"https:\/\/doi.org\/10.1145\/3604237.3626850","relation":{},"subject":[],"published":{"date-parts":[[2023,11,25]]},"assertion":[{"value":"2023-11-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}