{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T22:30:07Z","timestamp":1769553007790,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"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":[[2024,5,13]]},"DOI":"10.1145\/3589335.3651980","type":"proceedings-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T18:41:21Z","timestamp":1715539281000},"page":"1798-1802","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Towards Graph Foundation Models for Personalization"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7194-4155","authenticated-orcid":false,"given":"Andreas","family":"Damianou","sequence":"first","affiliation":[{"name":"Spotify, Cambridge, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9631-1799","authenticated-orcid":false,"given":"Francesco","family":"Fabbri","sequence":"additional","affiliation":[{"name":"Spotify, Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1589-9559","authenticated-orcid":false,"given":"Paul","family":"Gigioli","sequence":"additional","affiliation":[{"name":"Spotify, New York, NY, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8466-3933","authenticated-orcid":false,"given":"Marco","family":"De Nadai","sequence":"additional","affiliation":[{"name":"Spotify, Copenhagen, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8827-3780","authenticated-orcid":false,"given":"Alice","family":"Wang","sequence":"additional","affiliation":[{"name":"Spotify, New York, NY, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3898-7480","authenticated-orcid":false,"given":"Enrico","family":"Palumbo","sequence":"additional","affiliation":[{"name":"Spotify, Turin, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3531-3096","authenticated-orcid":false,"given":"Mounia","family":"Lalmas","sequence":"additional","affiliation":[{"name":"Spotify, London, United Kingdom"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258","author":"Bommasani R.","year":"2021","unstructured":"R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx, M. S. Bernstein, J. Bohg, A. Bosselut, E. Brunskill, et al. On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258, 2021."},{"key":"e_1_3_2_2_2_1","volume-title":"P. Shyam, G. Sastry, A. Askell, et al. Language models are few-shot learners. Advances in neural information processing systems, 33:1877--1901","author":"Brown T.","year":"2020","unstructured":"T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakan- tan, P. Shyam, G. Sastry, A. Askell, et al. Language models are few-shot learners. Advances in neural information processing systems, 33:1877--1901, 2020."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589335.3648339"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539080"},{"key":"e_1_3_2_2_5_1","volume-title":"Relational deep learning: Graph representation learning on relational databases. arXiv preprint arXiv:2312.04615","author":"Fey M.","year":"2023","unstructured":"M. Fey, W. Hu, K. Huang, J. E. Lenssen, R. Ranjan, J. Robinson, R. Ying, J. You, and J. Leskovec. Relational deep learning: Graph representation learning on relational databases. arXiv preprint arXiv:2312.04615, 2023."},{"key":"e_1_3_2_2_6_1","volume-title":"Towards foundation models for knowledge graph reasoning. arXiv preprint arXiv:2310.04562","author":"Galkin M.","year":"2023","unstructured":"M. Galkin, X. Yuan, H. Mostafa, J. Tang, and Z. Zhu. Towards foundation models for knowledge graph reasoning. arXiv preprint arXiv:2310.04562, 2023."},{"key":"e_1_3_2_2_7_1","volume-title":"Llark: A multimodal foundation model for music. arXiv preprint arXiv:2310.07160","author":"Gardner J.","year":"2023","unstructured":"J. Gardner, S. Durand, D. Stoller, and R. M. Bittner. Llark: A multimodal foundation model for music. arXiv preprint arXiv:2310.07160, 2023."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3546767"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403302"},{"key":"e_1_3_2_2_10_1","volume-title":"Inductive representation learning on large graphs. Advances in neural information processing systems, 30","author":"Hamilton W.","year":"2017","unstructured":"W. Hamilton, Z. Ying, and J. Leskovec. Inductive representation learning on large graphs. Advances in neural information processing systems, 30, 2017."},{"key":"e_1_3_2_2_11_1","volume-title":"Prodigy: Enabling in-context learning over graphs","author":"Huang Q.","year":"2023","unstructured":"Q. Huang, H. Ren, P. Chen, G. Kr?manc, D. Zeng, P. Liang, and J. Leskovec. Prodigy: Enabling in-context learning over graphs, 2023."},{"key":"e_1_3_2_2_12_1","volume-title":"Efficient and effective training of language and graph neural network models. arXiv preprint arXiv:2206.10781","author":"Ioannidis V. N.","year":"2022","unstructured":"V. N. Ioannidis, X. Song, D. Zheng, H. Zhang, J. Ma, Y. Xu, B. Zeng, T. Chilimbi, and G. Karypis. Efficient and effective training of language and graph neural network models. arXiv preprint arXiv:2206.10781, 2022."},{"key":"e_1_3_2_2_13_1","volume-title":"Towards graph foundation models: A survey and beyond. arXiv preprint arXiv:2310.11829","author":"Liu J.","year":"2023","unstructured":"J. Liu, C. Yang, Z. Lu, J. Chen, Y. Li, M. Zhang, T. Bai, Y. Fang, L. Sun, P. S. Yu, et al. Towards graph foundation models: A survey and beyond. arXiv preprint arXiv:2310.11829, 2023."},{"key":"e_1_3_2_2_14_1","volume-title":"Unified-io 2: Scaling autoregressive multimodal models with vision, language, audio, and action. arXiv preprint arXiv:2312.17172","author":"Lu J.","year":"2023","unstructured":"J. Lu, C. Clark, S. Lee, Z. Zhang, S. Khosla, R. Marten, D. Hoiem, and A. Kembhavi. Unified-io 2: Scaling autoregressive multimodal models with vision, language, audio, and action. arXiv preprint arXiv:2312.17172, 2023."},{"key":"e_1_3_2_2_15_1","volume-title":"Llm-rec: Personalized recommen-dation via prompting large language models. arXiv preprint arXiv:2307.15780","author":"Lyu H.","year":"2023","unstructured":"H. Lyu, S. Jiang, H. Zeng, Y. Xia, and J. Luo. Llm-rec: Personalized recommen-dation via prompting large language models. arXiv preprint arXiv:2307.15780, 2023."},{"key":"e_1_3_2_2_16_1","volume-title":"Graph foundation models","author":"Mao H.","year":"2024","unstructured":"H. Mao, Z. Chen, W. Tang, J. Zhao, Y. Ma, T. Zhao, N. Shah, M. Galkin, and J. Tang. Graph foundation models, 2024."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615481"},{"key":"e_1_3_2_2_18_1","volume-title":"Florence-2: Advancing a unified representation for a variety of vision tasks. arXiv preprint arXiv:2311.06242","author":"Xiao B.","year":"2023","unstructured":"B. Xiao, H. Wu, W. Xu, X. Dai, H. Hu, Y. Lu, M. Zeng, C. Liu, and L. Yuan. Florence-2: Advancing a unified representation for a variety of vision tasks. arXiv preprint arXiv:2311.06242, 2023."},{"key":"e_1_3_2_2_19_1","volume-title":"Graph-aware language model pre-training on a large graph corpus can help multiple graph applications. arXiv preprint arXiv:2306.02592","author":"Xie H.","year":"2023","unstructured":"H. Xie, D. Zheng, J. Ma, H. Zhang, V. N. Ioannidis, X. Song, Q. Ping, S. Wang, C. Yang, Y. Xu, et al. Graph-aware language model pre-training on a large graph corpus can help multiple graph applications. arXiv preprint arXiv:2306.02592, 2023."},{"key":"e_1_3_2_2_20_1","first-page":"37309","volume":"35","author":"Yasunaga M.","year":"2022","unstructured":"M. Yasunaga, A. Bosselut, H. Ren, X. Zhang, C. D. Manning, P. S. Liang, and J. Leskovec. Deep bidirectional language-knowledge graph pretraining. Advances in Neural Information Processing Systems, 35:37309--37323, 2022.","journal-title":"Deep bidirectional language-knowledge graph pretraining. Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3346996"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_23_1","volume-title":"et al. Florence: A new foundation model for computer vision. arXiv preprint arXiv:2111.11432","author":"Yuan L.","year":"2021","unstructured":"L. Yuan, D. Chen, Y.-L. Chen, N. Codella, X. Dai, J. Gao, H. Hu, X. Huang, B. Li, C. Li, et al. Florence: A new foundation model for computer vision. arXiv preprint arXiv:2111.11432, 2021."},{"key":"e_1_3_2_2_24_1","volume-title":"International conference on learning representations","author":"Zhang X.","year":"2021","unstructured":"X. Zhang, A. Bosselut, M. Yasunaga, H. Ren, P. Liang, C. D. Manning, and J. Leskovec. Greaselm: Graph reasoning enhanced language models. In International conference on learning representations, 2021."},{"key":"e_1_3_2_2_25_1","volume-title":"Collm: Integrating collaborative embeddings into large language models for recommendation. arXiv preprint arXiv:2310.19488","author":"Zhang Y.","year":"2023","unstructured":"Y. Zhang, F. Feng, J. Zhang, K. Bao, Q. Wang, and X. He. Collm: Integrating collaborative embeddings into large language models for recommendation. arXiv preprint arXiv:2310.19488, 2023."}],"event":{"name":"WWW '24: The ACM Web Conference 2024","location":"Singapore Singapore","acronym":"WWW '24","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Companion Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651980","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589335.3651980","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:38:23Z","timestamp":1755823103000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589335.3651980"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":25,"alternative-id":["10.1145\/3589335.3651980","10.1145\/3589335"],"URL":"https:\/\/doi.org\/10.1145\/3589335.3651980","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}