{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T11:48:05Z","timestamp":1774352885016,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T00:00:00Z","timestamp":1728345600000},"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":[[2024,10,8]]},"DOI":"10.1145\/3640457.3688185","type":"proceedings-article","created":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T15:39:28Z","timestamp":1728401968000},"page":"1010-1015","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5981-352X","authenticated-orcid":false,"given":"Chiyu","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Information, University of British Columbia, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4154-7910","authenticated-orcid":false,"given":"Yifei","family":"Sun","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5717-9318","authenticated-orcid":false,"given":"Minghao","family":"Wu","sequence":"additional","affiliation":[{"name":"Monash University, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1892-425X","authenticated-orcid":false,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3267-9383","authenticated-orcid":false,"given":"Jie","family":"Lei","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8590-2040","authenticated-orcid":false,"given":"Muhammad","family":"Abdul-Mageed","sequence":"additional","affiliation":[{"name":"The University of British Columbia, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8797-4646","authenticated-orcid":false,"given":"Rong","family":"Jin","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1556-5416","authenticated-orcid":false,"given":"Angli","family":"Liu","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9471-8063","authenticated-orcid":false,"given":"Ji","family":"Zhu","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9599-5301","authenticated-orcid":false,"given":"Sem","family":"Park","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0335-1964","authenticated-orcid":false,"given":"Ning","family":"Yao","sequence":"additional","affiliation":[{"name":"Meta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2489-200X","authenticated-orcid":false,"given":"Bo","family":"Long","sequence":"additional","affiliation":[{"name":"Meta, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,10,8]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"2023. Gemini: A Family of Highly Capable Multimodal Models. ArXiv preprint abs\/2312.11805","author":"Anil Rohan","year":"2023","unstructured":"Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew\u00a0M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy\u00a0P. Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul\u00a0Ronald Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Ana\u00efs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, and et al.2023. Gemini: A Family of Highly Capable Multimodal Models. ArXiv preprint abs\/2312.11805 (2023)."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.21105\/JOSS.04101"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.PATREC.2005.10.010"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1227"},{"key":"e_1_3_2_2_5_1","volume-title":"Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring.","author":"Humeau Samuel","year":"2019","unstructured":"Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2019. Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring."},{"key":"e_1_3_2_2_6_1","volume-title":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Yansong Feng and Els Lefever (Eds.). Association for Computational Linguistics","author":"Iana Andreea","year":"2023","unstructured":"Andreea Iana, Goran Glava\u0161, and Heiko Paulheim. 2023. NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Yansong Feng and Els Lefever (Eds.). Association for Computational Linguistics, Singapore, 296\u2013310."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.eacl-main.74"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_2_9_1","volume-title":"Mixtral of Experts. ArXiv preprint abs\/2401.04088","author":"Jiang Q.","year":"2024","unstructured":"Albert\u00a0Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra\u00a0Singh Chaplot, Diego de Las\u00a0Casas, Emma\u00a0Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, L\u00e9lio\u00a0Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven\u00a0Le Scao, Th\u00e9ophile Gervet, Thibaut Lavril, Thomas Wang, Timoth\u00e9e Lacroix, and William\u00a0El Sayed. 2024. Mixtral of Experts. ArXiv preprint abs\/2401.04088 (2024)."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_12_1","volume-title":"Legommenders: A Modular Framework for Recommender Systems.","author":"Liu Qijiong","year":"2023","unstructured":"Qijiong Liu. 2023. Legommenders: A Modular Framework for Recommender Systems."},{"key":"e_1_3_2_2_13_1","volume-title":"ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models.","author":"Liu Qijiong","year":"2023","unstructured":"Qijiong Liu, Nuo Chen, Tetsuya Sakai, and Xiao-Ming Wu. 2023. ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models."},{"key":"e_1_3_2_2_14_1","unstructured":"Rui Liu Bin Yin Ziyi Cao Qianchen Xia Yong Chen and Dell Zhang. 2023. PerCoNet: News Recommendation with Explicit Persona and Contrastive Learning."},{"key":"e_1_3_2_2_15_1","volume-title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv preprint abs\/1907.11692","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv preprint abs\/1907.11692 (2019)."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098108"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531778"},{"key":"e_1_3_2_2_21_1","article-title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","volume":"21","author":"Raffel Colin","year":"2020","unstructured":"Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter\u00a0J. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. J. Mach. Learn. Res. 21 (2020), 140:1\u2013140:67.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_2_22_1","volume-title":"Proceedings of The Eighth Text REtrieval Conference, TREC 1999","author":"Voorhees M.","year":"1999","unstructured":"Ellen\u00a0M. Voorhees. 1999. The TREC-8 Question Answering Track Report. In Proceedings of The Eighth Text REtrieval Conference, TREC 1999, Gaithersburg, Maryland, USA, November 17-19, 1999(NIST Special Publication, Vol.\u00a0500-246), Ellen\u00a0M. Voorhees and Donna\u00a0K. Harman (Eds.). National Institute of Standards and Technology (NIST)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3240369"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747149"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.754"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/536"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_28_1","unstructured":"Chuhan Wu Fangzhao Wu Tao Qi and Yongfeng Huang. 2021. Empowering News Recommendation with Pre-trained Language Models."},{"key":"e_1_3_2_2_29_1","volume-title":"Fastformer: Additive Attention Can Be All You Need.","author":"Wu Chuhan","year":"2021","unstructured":"Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang, and Xing Xie. 2021. Fastformer: Additive Attention Can Be All You Need."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.331"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-44195-0_23"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/462"}],"event":{"name":"RecSys '24: 18th ACM Conference on Recommender Systems","location":"Bari Italy","acronym":"RecSys '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGAI ACM Special Interest Group on Artificial Intelligence","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval","SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["18th ACM Conference on Recommender Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3640457.3688185","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3640457.3688185","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:58:33Z","timestamp":1750294713000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3640457.3688185"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,8]]},"references-count":32,"alternative-id":["10.1145\/3640457.3688185","10.1145\/3640457"],"URL":"https:\/\/doi.org\/10.1145\/3640457.3688185","relation":{},"subject":[],"published":{"date-parts":[[2024,10,8]]},"assertion":[{"value":"2024-10-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}