{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T22:25:46Z","timestamp":1776205546192,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":27,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,9,22]]},"DOI":"10.1145\/3705328.3748038","type":"proceedings-article","created":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T10:48:44Z","timestamp":1757155724000},"page":"626-631","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Let It Go? Not Quite: Addressing Item Cold Start in Sequential Recommendations with Content-Based Initialization"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1757-3379","authenticated-orcid":false,"given":"Anton","family":"Pembek","sequence":"first","affiliation":[{"name":"Sber AI Lab, Moscow, Russian Federation and Lomonosov Moscow State University (MSU), Moscow, Russian Federation"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7105-6003","authenticated-orcid":false,"given":"Artem","family":"Fatkulin","sequence":"additional","affiliation":[{"name":"Sber AI Lab, Moscow, Russian Federation and HSE University, Moscow, Russian Federation"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8961-6921","authenticated-orcid":false,"given":"Anton","family":"Klenitskiy","sequence":"additional","affiliation":[{"name":"Sber AI Lab, Moscow, Russian Federation"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1415-2004","authenticated-orcid":false,"given":"Alexey","family":"Vasilev","sequence":"additional","affiliation":[{"name":"Sber AI Lab, Moscow, Russian Federation and HSE University, Moscow, Russian Federation"}]}],"member":"320","published-online":{"date-parts":[[2025,9,7]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"publisher","unstructured":"Artun Boz Wouter Zorgdrager Zoe Kotti Jesse Harte Panos Louridas Vassilios Karakoidas Dietmar Jannach and Marios Fragkoulis. 2025. Improving sequential recommendations with llms. ACM Transactions on Recommender Systems (2025). 10.1145\/3711667","DOI":"10.1145\/3711667"},{"key":"e_1_3_3_2_3_2","unstructured":"Shaked Brody and Shoval Lagziel. 2024. SimRec: Mitigating the cold-start problem in sequential recommendation by integrating item similarity. (2024). https:\/\/www.amazon.science\/publications\/simrec-mitigating-the-cold-start-problem-in-sequential-recommendation-by-integrating-item-similarity"},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531897"},{"key":"e_1_3_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3705328.3748164"},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3610639"},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608839"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591732"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"publisher","unstructured":"Yitong Ji Aixin Sun Jie Zhang and Chenliang Li. 2023. A critical study on data leakage in recommender system offline evaluation. ACM Transactions on Information Systems 41 3 (2023) 1\u201327. 10.1145\/3569930","DOI":"10.1145\/3569930"},{"key":"e_1_3_3_2_10_2","doi-asserted-by":"publisher","unstructured":"Wei Jin Haitao Mao Zheng Li Haoming Jiang Chen Luo Hongzhi Wen Haoyu Han Hanqing Lu Zhengyang Wang Ruirui Li et\u00a0al. 2023. Amazon-m2: A multilingual multi-locale shopping session dataset for recommendation and text generation. Advances in Neural Information Processing Systems 36 (2023) 8006\u20138026. 10.5555\/3666122.3666473","DOI":"10.5555\/3666122.3666473"},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3610644"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1145\/3640457.3688195"},{"key":"e_1_3_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599519"},{"key":"e_1_3_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767755"},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3551477"},{"key":"e_1_3_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671655"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591931"},{"key":"e_1_3_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412489"},{"key":"e_1_3_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/3640457.3688172"},{"key":"e_1_3_3_2_22_2","doi-asserted-by":"publisher","unstructured":"Aaron Van\u00a0den Oord Sander Dieleman and Benjamin Schrauwen. 2013. Deep content-based music recommendation. Advances in neural information processing systems 26 (2013). 10.5555\/2999792.2999907","DOI":"10.5555\/2999792.2999907"},{"key":"e_1_3_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/3640457.3691701"},{"key":"e_1_3_3_2_24_2","doi-asserted-by":"publisher","unstructured":"Maksims Volkovs Guangwei Yu and Tomi Poutanen. 2017. Dropoutnet: Addressing cold start in recommender systems. Advances in neural information processing systems 30 (2017). 10.5555\/3295222.3295249","DOI":"10.5555\/3295222.3295249"},{"key":"e_1_3_3_2_25_2","doi-asserted-by":"publisher","unstructured":"Liang Wang Nan Yang Xiaolong Huang Binxing Jiao Linjun Yang Daxin Jiang Rangan Majumder and Furu Wei. 2022. Text Embeddings by Weakly-Supervised Contrastive Pre-training. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2212.03533 (2022). 10.48550\/arXiv.2212.03533","DOI":"10.48550\/arXiv.2212.03533"},{"key":"e_1_3_3_2_26_2","doi-asserted-by":"publisher","unstructured":"Shiyu Wang Hao Ding Yupeng Gu Sergul Aydore Kousha Kalantari and Branislav Kveton. 2024. Language-Model Prior Overcomes Cold-Start Items. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2411.09065 (2024). 10.48550\/arXiv.2411.09065","DOI":"10.48550\/arXiv.2411.09065"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475665"},{"key":"e_1_3_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462843"}],"event":{"name":"RecSys '25: Nineteenth ACM Conference on Recommender Systems","location":"Prague Czech Republic","acronym":"RecSys '25","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGAI ACM Special Interest Group on Artificial Intelligence","SIGIR ACM Special Interest Group on Information Retrieval","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the Nineteenth ACM Conference on Recommender Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3705328.3748038","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T11:48:34Z","timestamp":1757159314000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3705328.3748038"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,7]]},"references-count":27,"alternative-id":["10.1145\/3705328.3748038","10.1145\/3705328"],"URL":"https:\/\/doi.org\/10.1145\/3705328.3748038","relation":{},"subject":[],"published":{"date-parts":[[2025,9,7]]},"assertion":[{"value":"2025-09-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}