{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:11:57Z","timestamp":1780636317955,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":59,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"Hong Kong Polytechnic University","doi-asserted-by":"publisher","award":["P0045485"],"award-info":[{"award-number":["P0045485"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"National Science and Technology Major Project","doi-asserted-by":"publisher","award":["2023ZD0121102"],"award-info":[{"award-number":["2023ZD0121102"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21B2026, 62302321"],"award-info":[{"award-number":["U21B2026, 62302321"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,7,10]]},"DOI":"10.1145\/3626772.3657690","type":"proceedings-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T12:40:05Z","timestamp":1720701605000},"page":"1785-1795","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":92,"title":["LLaRA: Large Language-Recommendation Assistant"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7998-8462","authenticated-orcid":false,"given":"Jiayi","family":"Liao","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8986-7965","authenticated-orcid":false,"given":"Sihang","family":"Li","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8094-0978","authenticated-orcid":false,"given":"Zhengyi","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6941-5218","authenticated-orcid":false,"given":"Jiancan","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8243-4683","authenticated-orcid":false,"given":"Yancheng","family":"Yuan","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6148-6329","authenticated-orcid":false,"given":"Xiang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8472-7992","authenticated-orcid":false,"given":"Xiangnan","family":"He","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Jean-Baptiste Alayrac Jeff Donahue Pauline Luc Antoine Miech Iain Barr Yana Hasson Karel Lenc Arthur Mensch Katherine Millican Malcolm Reynolds Roman Ring Eliza Rutherford Serkan Cabi Tengda Han Zhitao Gong Sina Samangooei Marianne Monteiro Jacob L. Menick Sebastian Borgeaud Andy Brock Aida Nematzadeh Sahand Sharifzadeh Mikolaj Binkowski Ricardo Barreira Oriol Vinyals Andrew Zisserman and Kar\u00e9n Simonyan. 2022. Flamingo: a Visual Language Model for Few-Shot Learning. In NeurIPS."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Keqin Bao Jizhi Zhang Yang Zhang Wenjie Wang Fuli Feng and Xiangnan He. 2023. TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. In RecSys. ACM 1007--1014.","DOI":"10.1145\/3604915.3608857"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"e_1_3_2_1_4_1","unstructured":"Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell Sandhini Agarwal Ariel Herbert-Voss Gretchen Krueger Tom Henighan Rewon Child Aditya Ramesh Daniel M. Ziegler Jeffrey Wu Clemens Winter Christopher Hesse Mark Chen Eric Sigler Mateusz Litwin Scott Gray Benjamin Chess Jack Clark Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever and Dario Amodei. 2020. Language Models are Few-Shot Learners. In NeurIPS."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2043932.2044016"},{"key":"e_1_3_2_1_6_1","volume-title":"Xing","author":"Chiang Wei-Lin","year":"2023","unstructured":"Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023. Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality. https:\/\/lmsys.org\/blog\/2023-03-30-vicuna\/"},{"key":"e_1_3_2_1_7_1","unstructured":"Jiaxi Cui Zongjian Li Yang Yan Bohua Chen and Li Yuan. 2023. ChatLaw: Open-Source Legal Large Language Model with Integrated External Knowledge Bases. arxiv: 2306.16092 [cs.CL]"},{"key":"e_1_3_2_1_8_1","volume-title":"M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems. CoRR","author":"Cui Zeyu","year":"2022","unstructured":"Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang. 2022. M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems. CoRR, Vol. abs\/2205.08084 (2022)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Sunhao Dai Ninglu Shao Haiyuan Zhao Weijie Yu Zihua Si Chen Xu Zhongxiang Sun Xiao Zhang and Jun Xu. 2023. Uncovering ChatGPT's Capabilities in Recommender Systems. In RecSys. ACM 1126--1132.","DOI":"10.1145\/3604915.3610646"},{"key":"e_1_3_2_1_10_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL-HLT (1)","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. In NAACL-HLT (1). Association for Computational Linguistics, 4171--4186."},{"key":"e_1_3_2_1_11_1","volume-title":"ICML (Proceedings of Machine Learning Research","volume":"8488","author":"Driess Danny","year":"2023","unstructured":"Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, and Pete Florence. 2023. PaLM-E: An Embodied Multimodal Language Model. In ICML (Proceedings of Machine Learning Research, Vol. 202). PMLR, 8469--8488."},{"key":"e_1_3_2_1_12_1","article-title":"Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations","volume":"39","author":"Fang Hui","year":"2020","unstructured":"Hui Fang, Danning Zhang, Yiheng Shu, and Guibing Guo. 2020. Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations. ACM Trans. Inf. Syst., Vol. 39, 1 (2020), 10:1--10:42.","journal-title":"ACM Trans. Inf. Syst."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Shijie Geng Shuchang Liu Zuohui Fu Yingqiang Ge and Yongfeng Zhang. 2022. Recommendation as Language Processing (RLP): A Unified Pretrain Personalized Prompt & Predict Paradigm (P5). In RecSys. ACM 299--315.","DOI":"10.1145\/3523227.3546767"},{"key":"e_1_3_2_1_14_1","article-title":"The MovieLens Datasets","volume":"5","author":"Maxwell Harper F.","year":"2016","unstructured":"F. Maxwell Harper and Joseph A. Konstan. 2016. The MovieLens Datasets: History and Context. ACM Trans. Interact. Intell. Syst., Vol. 5, 4 (2016), 19:1--19:19.","journal-title":"History and Context. ACM Trans. Interact. Intell. Syst."},{"key":"e_1_3_2_1_15_1","volume-title":"International Conference on Learning Representations.","author":"He Junxian","year":"2021","unstructured":"Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, and Graham Neubig. 2021. Towards a Unified View of Parameter-Efficient Transfer Learning. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_16_1","unstructured":"Bal\u00e1zs Hidasi Alexandros Karatzoglou Linas Baltrunas and Domonkos Tikk. 2016. Session-based Recommendations with Recurrent Neural Networks. In ICLR (Poster)."},{"key":"e_1_3_2_1_17_1","volume-title":"3D-LLM: Injecting the 3D World into Large Language Models. arXiv preprint arXiv:2307.12981","author":"Hong Yining","year":"2023","unstructured":"Yining Hong, Haoyu Zhen, Peihao Chen, Shuhong Zheng, Yilun Du, Zhenfang Chen, and Chuang Gan. 2023. 3D-LLM: Injecting the 3D World into Large Language Models. arXiv preprint arXiv:2307.12981 (2023)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Yupeng Hou Zhankui He Julian J. McAuley and Wayne Xin Zhao. 2023a. Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders. In WWW. ACM 1162--1171.","DOI":"10.1145\/3543507.3583434"},{"key":"e_1_3_2_1_19_1","volume-title":"Yaliang Li, Bolin Ding, and Ji-Rong Wen.","author":"Hou Yupeng","year":"2022","unstructured":"Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, and Ji-Rong Wen. 2022. Towards Universal Sequence Representation Learning for Recommender Systems. In KDD. ACM, 585--593."},{"key":"e_1_3_2_1_20_1","volume-title":"Large Language Models are Zero-Shot Rankers for Recommender Systems. CoRR","author":"Hou Yupeng","year":"2023","unstructured":"Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian J. McAuley, and Wayne Xin Zhao. 2023b. Large Language Models are Zero-Shot Rankers for Recommender Systems. CoRR, Vol. abs\/2305.08845 (2023)."},{"key":"e_1_3_2_1_21_1","unstructured":"Edward J. Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang and Weizhu Chen. 2022. LoRA: Low-Rank Adaptation of Large Language Models. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_22_1","volume-title":"How to Index Item IDs for Recommendation Foundation Models. CoRR","author":"Hua Wenyue","year":"2023","unstructured":"Wenyue Hua, Shuyuan Xu, Yingqiang Ge, and Yongfeng Zhang. 2023. How to Index Item IDs for Recommendation Foundation Models. CoRR, Vol. abs\/2305.06569 (2023)."},{"key":"e_1_3_2_1_23_1","volume-title":"Music, Sound, and Talking Head. CoRR","author":"Huang Rongjie","year":"2023","unstructured":"Rongjie Huang, Mingze Li, Dongchao Yang, Jiatong Shi, Xuankai Chang, Zhenhui Ye, Yuning Wu, Zhiqing Hong, Jiawei Huang, Jinglin Liu, Yi Ren, Zhou Zhao, and Shinji Watanabe. 2023. AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head. CoRR, Vol. abs\/2304.12995 (2023)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3569930"},{"key":"e_1_3_2_1_25_1","volume-title":"McAuley","author":"Kang Wang-Cheng","year":"2018","unstructured":"Wang-Cheng Kang and Julian J. McAuley. 2018. Self-Attentive Sequential Recommendation. In ICDM. IEEE Computer Society, 197--206."},{"key":"e_1_3_2_1_26_1","volume-title":"EMNLP (1)","author":"Lester Brian","unstructured":"Brian Lester, Rami Al-Rfou, and Noah Constant. 2021. The Power of Scale for Parameter-Efficient Prompt Tuning. In EMNLP (1). Association for Computational Linguistics, 3045--3059."},{"key":"e_1_3_2_1_27_1","volume-title":"Hoi","author":"Li Junnan","year":"2023","unstructured":"Junnan Li, Dongxu Li, Silvio Savarese, and Steven C. H. Hoi. 2023a. BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models. CoRR, Vol. abs\/2301.12597 (2023)."},{"key":"e_1_3_2_1_28_1","volume-title":"McAuley","author":"Li Jiacheng","year":"2023","unstructured":"Jiacheng Li, Ming Wang, Jin Li, Jinmiao Fu, Xin Shen, Jingbo Shang, and Julian J. McAuley. 2023b. Text Is All You Need: Learning Language Representations for Sequential Recommendation. In KDD. ACM, 1258--1267."},{"key":"e_1_3_2_1_29_1","volume-title":"The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=xI4yNlkaqh","author":"Li Sihang","year":"2024","unstructured":"Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, and Qi Tian. 2024. Towards 3D Molecule-Text Interpretation in Language Models. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=xI4yNlkaqh"},{"key":"e_1_3_2_1_30_1","unstructured":"Yangguang Li Feng Liang Lichen Zhao Yufeng Cui Wanli Ouyang Jing Shao Fengwei Yu and Junjie Yan. 2022. Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_31_1","volume-title":"How Can Recommender Systems Benefit from Large Language Models: A Survey. CoRR","author":"Lin Jianghao","year":"2023","unstructured":"Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, and Weinan Zhang. 2023. How Can Recommender Systems Benefit from Large Language Models: A Survey. CoRR, Vol. abs\/2306.05817 (2023)."},{"key":"e_1_3_2_1_32_1","volume-title":"Is ChatGPT a Good Recommender? A Preliminary Study. CoRR","author":"Liu Junling","year":"2023","unstructured":"Junling Liu, Chao Liu, Renjie Lv, Kang Zhou, and Yan Zhang. 2023b. Is ChatGPT a Good Recommender? A Preliminary Study. CoRR, Vol. abs\/2304.10149 (2023)."},{"key":"e_1_3_2_1_33_1","volume-title":"abs\/2103.10385","author":"Liu Xiao","year":"2021","unstructured":"Xiao Liu, Yanan Zheng, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, and Jie Tang. 2021. GPT Understands, Too. CoRR, Vol. abs\/2103.10385 (2021)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Zhiyuan Liu Sihang Li Yanchen Luo Hao Fei Yixin Cao Kenji Kawaguchi Xiang Wang and Tat-Seng Chua. 2023a. MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. In EMNLP. Association for Computational Linguistics 15623--15638.","DOI":"10.18653\/v1\/2023.emnlp-main.966"},{"key":"e_1_3_2_1_35_1","volume-title":"Audio, Video, and Text Integration. arXiv","author":"Lyu Chenyang","year":"2023","unstructured":"Chenyang Lyu, Minghao Wu, Longyue Wang, Xinting Huang, Bingshuai Liu, Zefeng Du, Shuming Shi, and Zhaopeng Tu. 2023. Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration. arXiv (2023)."},{"key":"e_1_3_2_1_36_1","unstructured":"OpenAI. 2023. GPT-4 Technical Report. CoRR Vol. abs\/2303.08774 (2023)."},{"key":"e_1_3_2_1_37_1","unstructured":"Long Ouyang Jeffrey Wu Xu Jiang Diogo Almeida Carroll L. Wainwright Pamela Mishkin Chong Zhang Sandhini Agarwal Katarina Slama Alex Ray John Schulman Jacob Hilton Fraser Kelton Luke Miller Maddie Simens Amanda Askell Peter Welinder Paul F. Christiano Jan Leike and Ryan Lowe. 2022. Training language models to follow instructions with human feedback. In NeurIPS."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Massimo Quadrana Alexandros Karatzoglou Bal\u00e1zs Hidasi and Paolo Cremonesi. 2017. Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. In RecSys. ACM 130--137.","DOI":"10.1145\/3109859.3109896"},{"key":"e_1_3_2_1_39_1","volume-title":"ICML (Proceedings of Machine Learning Research","volume":"8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. In ICML (Proceedings of Machine Learning Research, Vol. 139). PMLR, 8748--8763."},{"key":"e_1_3_2_1_40_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 J. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. J. Mach. Learn. Res., Vol. 21 (2020), 140:1-140:67.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Karan Singhal Shekoofeh Azizi Tao Tu S. Sara Mahdavi Jason Wei Hyung Won Chung Nathan Scales Ajay Tanwani Heather Cole-Lewis Stephen Pfohl Perry Payne Martin Seneviratne Paul Gamble Chris Kelly Nathaneal Scharli Aakanksha Chowdhery Philip Mansfield Blaise Aguera y Arcas Dale Webster Greg S. Corrado Yossi Matias Katherine Chou Juraj Gottweis Nenad Tomasev Yun Liu Alvin Rajkomar Joelle Barral Christopher Semturs Alan Karthikesalingam and Vivek Natarajan. 2022. Large Language Models Encode Clinical Knowledge. arxiv: 2212.13138 [cs.CL]","DOI":"10.1038\/s41586-023-06455-0"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Fei Sun Jun Liu Jian Wu Changhua Pei Xiao Lin Wenwu Ou and Peng Jiang. 2019. BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer. In CIKM. ACM 1441--1450.","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Yong Kiam Tan Xinxing Xu and Yong Liu. 2016. Improved Recurrent Neural Networks for Session-based Recommendations. In DLRS@RecSys. ACM 17--22.","DOI":"10.1145\/2988450.2988452"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Jiaxi Tang and Ke Wang. 2018. Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding. In WSDM. ACM 565--573.","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_1_45_1","volume-title":"LLaMA: Open and Efficient Foundation Language Models. CoRR","author":"Touvron Hugo","year":"2023","unstructured":"Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth\u00e9e Lacroix, Baptiste Rozi\u00e8re, Naman Goyal, Eric Hambro, Faisal Azhar, Aur\u00e9lien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023a. LLaMA: Open and Efficient Foundation Language Models. CoRR, Vol. abs\/2302.13971 (2023)."},{"key":"e_1_3_2_1_46_1","unstructured":"Hugo Touvron Louis Martin Kevin Stone Peter Albert Amjad Almahairi Yasmine Babaei Nikolay Bashlykov Soumya Batra Prajjwal Bhargava Shruti Bhosale Dan Bikel Lukas Blecher Cristian Canton-Ferrer Moya Chen Guillem Cucurull David Esiobu Jude Fernandes Jeremy Fu Wenyin Fu Brian Fuller Cynthia Gao Vedanuj Goswami Naman Goyal Anthony Hartshorn Saghar Hosseini Rui Hou Hakan Inan Marcin Kardas Viktor Kerkez Madian Khabsa Isabel Kloumann Artem Korenev Punit Singh Koura Marie-Anne Lachaux Thibaut Lavril Jenya Lee Diana Liskovich Yinghai Lu Yuning Mao Xavier Martinet Todor Mihaylov Pushkar Mishra Igor Molybog Yixin Nie Andrew Poulton Jeremy Reizenstein Rashi Rungta Kalyan Saladi Alan Schelten Ruan Silva Eric Michael Smith Ranjan Subramanian Xiaoqing Ellen Tan Binh Tang Ross Taylor Adina Williams Jian Xiang Kuan Puxin Xu Zheng Yan Iliyan Zarov Yuchen Zhang Angela Fan Melanie Kambadur Sharan Narang Aur\u00e9lien Rodriguez Robert Stojnic Sergey Edunov and Thomas Scialom. 2023b. Llama 2: Open Foundation and Fine-Tuned Chat Models. CoRR Vol. abs\/2307.09288 (2023)."},{"key":"e_1_3_2_1_47_1","unstructured":"Maria Tsimpoukelli Jacob Menick Serkan Cabi S. M. Ali Eslami Oriol Vinyals and Felix Hill. 2021. Multimodal Few-Shot Learning with Frozen Language Models. In NeurIPS. 200--212."},{"key":"e_1_3_2_1_48_1","volume-title":"Orgun","author":"Wang Shoujin","year":"2019","unstructured":"Shoujin Wang, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, and Mehmet A. Orgun. 2019. Sequential Recommender Systems: Challenges, Progress and Prospects. In IJCAI. ijcai.org, 6332--6338."},{"key":"e_1_3_2_1_49_1","first-page":"4555","article-title":"A Survey on Curriculum Learning","volume":"44","author":"Wang Xin","year":"2022","unstructured":"Xin Wang, Yudong Chen, and Wenwu Zhu. 2022. A Survey on Curriculum Learning. IEEE Trans. Pattern Anal. Mach. Intell., Vol. 44, 9 (2022), 4555--4576.","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"e_1_3_2_1_50_1","volume-title":"A Survey on Large Language Models for Recommendation. CoRR","author":"Wu Likang","year":"1986","unstructured":"Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, and Enhong Chen. 2023b. A Survey on Large Language Models for Recommendation. CoRR, Vol. abs\/2305.19860 (2023)."},{"key":"e_1_3_2_1_51_1","volume-title":"BloombergGPT: A Large Language Model for Finance. CoRR","author":"Wu Shijie","year":"2023","unstructured":"Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David S. Rosenberg, and Gideon Mann. 2023a. BloombergGPT: A Large Language Model for Finance. CoRR, Vol. abs\/2303.17564 (2023)."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Zhengyi Yang Xiangnan He Jizhi Zhang Jiancan Wu Xin Xin Jiawei Chen and Xiang Wang. 2023. A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. In SIGIR. ACM 331--340.","DOI":"10.1145\/3539618.3591624"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"crossref","unstructured":"Fajie Yuan Alexandros Karatzoglou Ioannis Arapakis Joemon M. Jose and Xiangnan He. 2019. A Simple Convolutional Generative Network for Next Item Recommendation. In WSDM. ACM 582--590.","DOI":"10.1145\/3289600.3290975"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"crossref","unstructured":"Zheng Yuan Fajie Yuan Yu Song Youhua Li Junchen Fu Fei Yang Yunzhu Pan and Yongxin Ni. 2023. Where to Go Next for Recommender Systems? ID-vs. Modality-based Recommender Models Revisited. In SIGIR. ACM 2639--2649.","DOI":"10.1145\/3539618.3591932"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"crossref","unstructured":"An Zhang Yuxin Chen Leheng Sheng Xiang Wang and Tat-Seng Chua. 2024. On Generative Agents in Recommendation. In SIGIR.","DOI":"10.1145\/3626772.3657844"},{"key":"e_1_3_2_1_56_1","volume-title":"Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding. arXiv","author":"Zhang Hang","year":"2023","unstructured":"Hang Zhang, Xin Li, and Lidong Bing. 2023b. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding. arXiv (2023)."},{"key":"e_1_3_2_1_57_1","volume-title":"CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation. CoRR","author":"Zhang Yang","year":"1948","unstructured":"Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, and Xiangnan He. 2023a. CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation. CoRR, Vol. abs\/2310.19488 (2023)."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"crossref","unstructured":"Yuyue Zhao Jiancan Wu Xiang Wang Wei Tang Dingxian Wang and Maarten de Rijke. 2024. Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning. In SIGIR.","DOI":"10.1145\/3626772.3657828"},{"key":"e_1_3_2_1_59_1","volume-title":"Minigpt-4: Enhancing vision-language understanding with advanced large language models. arXiv preprint arXiv:2304.10592","author":"Zhu Deyao","year":"2023","unstructured":"Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny. 2023. Minigpt-4: Enhancing vision-language understanding with advanced large language models. arXiv preprint arXiv:2304.10592 (2023)."}],"event":{"name":"SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Washington DC USA","acronym":"SIGIR 2024","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657690","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3626772.3657690","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:39:50Z","timestamp":1755841190000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657690"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,10]]},"references-count":59,"alternative-id":["10.1145\/3626772.3657690","10.1145\/3626772"],"URL":"https:\/\/doi.org\/10.1145\/3626772.3657690","relation":{},"subject":[],"published":{"date-parts":[[2024,7,10]]},"assertion":[{"value":"2024-07-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}