{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T16:04:38Z","timestamp":1780675478895,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":76,"publisher":"ACM","funder":[{"name":"the Specific Research Project of Guangxi for Research Bases and Talents","award":["GuiKe AD24010011"],"award-info":[{"award-number":["GuiKe AD24010011"]}]},{"name":"the Key Research & Development Program Project of Guangxi","award":["GuiKe AB25069095"],"award-info":[{"award-number":["GuiKe AB25069095"]}]},{"name":"the Australian Research Council","award":["DP230101122"],"award-info":[{"award-number":["DP230101122"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792364","type":"proceedings-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T21:54:34Z","timestamp":1775771674000},"page":"3870-3880","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Beyond Factual Queries: A Novel Predictive Retrieval-Augmented Generation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0383-1462","authenticated-orcid":false,"given":"Debo","family":"Cheng","sequence":"first","affiliation":[{"name":"Hainan University, Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-3714-3474","authenticated-orcid":false,"given":"Jianfeng","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Computer, Electronics and Information, Guangxi University, Nanning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5506-8913","authenticated-orcid":false,"given":"Qingfeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Guangxi University, Nanning, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8605-7856","authenticated-orcid":false,"given":"Jinyi","family":"Jie","sequence":"additional","affiliation":[{"name":"Hainan University, Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4172-5908","authenticated-orcid":false,"given":"Jiangzhang","family":"Gan","sequence":"additional","affiliation":[{"name":"Hainan University, Haikou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al.","author":"Achiam Josh","year":"2023","unstructured":"Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al., 2023. Gpt-4 technical report. arXiv preprint arXiv:2303.08774 (2023)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Jean-Baptiste Alayrac Jeff Donahue Pauline Luc Antoine Miech Iain Barr Yana Hasson Karel Lenc Arthur Mensch Katherine Millican Malcolm Reynolds et al. 2022. Flamingo: a visual language model for few-shot learning. Advances in neural information processing systems Vol. 35 (2022) 23716-23736.","DOI":"10.52202\/068431-1723"},{"key":"e_1_3_2_1_3_1","volume-title":"Self-rag: Learning to retrieve, generate, and critique through self-reflection.","author":"Asai Akari","year":"2024","unstructured":"Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2024. Self-rag: Learning to retrieve, generate, and critique through self-reflection. (2024)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608857"},{"key":"e_1_3_2_1_5_1","volume-title":"International conference on machine learning. PMLR, 2206-2240","author":"Borgeaud Sebastian","year":"2022","unstructured":"Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, et al., 2022. Improving language models by retrieving from trillions of tokens. In International conference on machine learning. PMLR, 2206-2240."},{"key":"e_1_3_2_1_6_1","volume-title":"Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al.","author":"Chen Mark","year":"2021","unstructured":"Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al., 2021. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2025.104429"},{"key":"e_1_3_2_1_8_1","volume-title":"Uncertainty-Aware Graph Neural Networks: A Multihop Evidence Fusion Approach","author":"Chen Qingfeng","year":"2025","unstructured":"Qingfeng Chen, Shiyuan Li, Yixin Liu, Shirui Pan, Geoffrey I Webb, and Shichao Zhang. 2025. Uncertainty-Aware Graph Neural Networks: A Multihop Evidence Fusion Approach. IEEE Transactions on Neural Networks and Learning Systems (2025)."},{"key":"e_1_3_2_1_9_1","volume-title":"Uprise: Universal prompt retrieval for improving zero-shot evaluation. arXiv preprint arXiv:2303.08518","author":"Cheng Daixuan","year":"2023","unstructured":"Daixuan Cheng, Shaohan Huang, Junyu Bi, Yuefeng Zhan, Jianfeng Liu, Yujing Wang, Hao Sun, Furu Wei, Denvy Deng, and Qi Zhang. 2023a. Uprise: Universal prompt retrieval for improving zero-shot evaluation. arXiv preprint arXiv:2303.08518 (2023)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1899"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Sunhao Dai et al. 2023a. Uncovering ChatGPT's Capabilities in Recommender Systems. In RecSys Jie Zhang Li Chen Shlomo Berkovsky Min Zhang Tommaso Di Noia Justin Basilico Luiz Pizzato and Yang Song (Eds.). 1126-1132.","DOI":"10.1145\/3604915.3610646"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3610646"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3746252.3761177"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.emnlp-main.1491"},{"key":"e_1_3_2_1_15_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","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. Association for Computational Linguistics, 4171-4186."},{"key":"e_1_3_2_1_16_1","volume-title":"A Large Language Model Enhanced Conversational Recommender System. CoRR","author":"Feng Yue","year":"2023","unstructured":"Yue Feng, Shuchang Liu, Zhenghai Xue, Qingpeng Cai, Lantao Hu, Peng Jiang, Kun Gai, and Fei Sun. 2023. A Large Language Model Enhanced Conversational Recommender System. CoRR, Vol. abs\/2308.06212 (2023)."},{"key":"e_1_3_2_1_17_1","volume-title":"Konstan","author":"Maxwell F.","year":"2015","unstructured":"F.Maxwell and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context.. In ACM Transactions on Interactive Intelligent Systems (TiiS)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.99"},{"key":"e_1_3_2_1_19_1","volume-title":"Chat-rec: Towards interactive and explainable llms-augmented recommender system. arXiv","author":"Gao Yunfan","year":"2023","unstructured":"Yunfan Gao, Tao Sheng, Youlin Xiang, Yun Xiong, Haofen Wang, and Jiawei Zhang. 2023b. Chat-rec: Towards interactive and explainable llms-augmented recommender system. arXiv (2023)."},{"key":"e_1_3_2_1_20_1","volume-title":"Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997","author":"Gao Yunfan","year":"2023","unstructured":"Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yixin Dai, Jiawei Sun, Haofen Wang, and Haofen Wang. 2023c. Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997, Vol. 2, 1 (2023)."},{"key":"e_1_3_2_1_21_1","volume-title":"ChatGPT is not all you need. A State of the Art Review of large Generative AI models. arXiv preprint arXiv:2301.04655","author":"Gozalo-Brizuela Roberto","year":"2023","unstructured":"Roberto Gozalo-Brizuela and Eduardo C Garrido-Merchan. 2023. ChatGPT is not all you need. A State of the Art Review of large Generative AI models. arXiv preprint arXiv:2301.04655 (2023)."},{"key":"e_1_3_2_1_22_1","volume-title":"International conference on machine learning. PMLR, 3929-3938","author":"Guu Kelvin","year":"2020","unstructured":"Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020. Retrieval augmented language model pre-training. In International conference on machine learning. PMLR, 3929-3938."},{"key":"e_1_3_2_1_23_1","volume-title":"The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis)","author":"Maxwell Harper F","year":"2015","unstructured":"F Maxwell Harper and Joseph A Konstan. 2015. The movielens datasets: History and context. Acm transactions on interactive intelligent systems (tiis), Vol. 5, 4 (2015), 1-19."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2872427.2883037"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_26_1","unstructured":"Bal\u00e1zs Hidasi et al. 2016. Session-based Recommendations with Recurrent Neural Networks. In ICLR."},{"key":"e_1_3_2_1_27_1","first-page":"2790","volume-title":"Proceedings of the 36th International Conference on Machine Learning, ICML 2019","volume":"97","author":"Houlsby Neil","year":"2019","unstructured":"Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, et al., 2019. Parameter-Efficient Transfer Learning for NLP. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Vol. 97. 2790-2799."},{"key":"e_1_3_2_1_28_1","first-page":"3","article-title":"Lora: Low-rank adaptation of large language models","volume":"1","author":"Hu Edward J","year":"2022","unstructured":"Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al., 2022. Lora: Low-rank adaptation of large language models. ICLR, Vol. 1, 2 (2022), 3.","journal-title":"ICLR"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3703155"},{"key":"e_1_3_2_1_30_1","first-page":"1","article-title":"Atlas: Few-shot learning with retrieval augmented language models","volume":"24","author":"Izacard Gautier","year":"2023","unstructured":"Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2023. Atlas: Few-shot learning with retrieval augmented language models. Journal of Machine Learning Research, Vol. 24, 251 (2023), 1-43.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_31_1","volume-title":"Andrea Madotto, and Pascale Fung.","author":"Ji Ziwei","year":"2023","unstructured":"Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023. Survey of hallucination in natural language generation. ACM computing surveys, Vol. 55, 12 (2023), 1-38."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.495"},{"key":"e_1_3_2_1_33_1","volume-title":"Jinheon Baek, and Sung Ju Hwang.","author":"Kang Minki","year":"2023","unstructured":"Minki Kang, Jin Myung Kwak, Jinheon Baek, and Sung Ju Hwang. 2023. Knowledge graph-augmented language models for knowledge-grounded dialogue generation. arXiv preprint arXiv:2305.18846 (2023)."},{"key":"e_1_3_2_1_34_1","first-page":"197","article-title":"Self-attentive sequential recommendation","author":"Kang Wang-Cheng","year":"2018","unstructured":"Wang-Cheng Kang and Julian McAuley. 2018. Self-attentive sequential recommendation. In ICDM. 197-206.","journal-title":"ICDM."},{"key":"e_1_3_2_1_35_1","volume-title":"Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.","author":"Karpukhin Vladimir","year":"2020","unstructured":"Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick SH Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020. Dense Passage Retrieval for Open-Domain Question Answering.. In EMNLP (1). 6769-6781."},{"key":"e_1_3_2_1_36_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In ICLR."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"e_1_3_2_1_39_1","unstructured":"Patrick Lewis Ethan Perez Aleksandra Piktus Fabio Petroni Vladimir Karpukhin Naman Goyal Heinrich K\u00fcttler Mike Lewis Wen-tau Yih Tim Rockt\u00e4schel et al. 2020. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in neural information processing systems Vol. 33 (2020) 9459-9474."},{"key":"e_1_3_2_1_40_1","volume-title":"International conference on machine learning. PMLR","author":"Li Junnan","year":"2023","unstructured":"Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023b. Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In International conference on machine learning. PMLR, 19730-19742."},{"key":"e_1_3_2_1_41_1","volume-title":"E4srec: An elegant effective efficient extensible solution of large language models for sequential recommendation. arXiv preprint arXiv:2312.02443","author":"Li Xinhang","year":"2023","unstructured":"Xinhang Li, Chong Chen, Xiangyu Zhao, Yong Zhang, and Chunxiao Xing. 2023a. E4srec: An elegant effective efficient extensible solution of large language models for sequential recommendation. arXiv preprint arXiv:2312.02443 (2023)."},{"key":"e_1_3_2_1_42_1","volume-title":"Bosheng Ding, Shafiq Joty, Soujanya Poria, and Lidong Bing.","author":"Li Xingxuan","year":"2023","unstructured":"Xingxuan Li, Ruochen Zhao, Yew Ken Chia, Bosheng Ding, Shafiq Joty, Soujanya Poria, and Lidong Bing. 2023c. Chain-of-knowledge: Grounding large language models via dynamic knowledge adapting over heterogeneous sources. arXiv preprint arXiv:2305.13269 (2023)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.353"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3701716.3715240"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657690"},{"key":"e_1_3_2_1_46_1","volume-title":"The Twelfth International Conference on Learning Representations.","author":"Lin Xi Victoria","year":"2023","unstructured":"Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Richard James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, et al., 2023. Ra-dit: Retrieval-augmented dual instruction tuning. In The Twelfth International Conference on Learning Representations."},{"key":"e_1_3_2_1_47_1","volume-title":"Visual instruction tuning. Advances in neural information processing systems","author":"Liu Haotian","year":"2023","unstructured":"Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023a. Visual instruction tuning. Advances in neural information processing systems, Vol. 36 (2023), 34892-34916."},{"key":"e_1_3_2_1_48_1","volume-title":"Is chatgpt a good recommender? a preliminary study. arXiv:2304.10149","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. arXiv:2304.10149 (2023)."},{"key":"e_1_3_2_1_49_1","first-page":"50772","article-title":"Arc: A generalist graph anomaly detector with in-context learning","volume":"37","author":"Liu Yixin","year":"2024","unstructured":"Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, and Shirui Pan. 2024. Arc: A generalist graph anomaly detector with in-context learning. Advances in Neural Information Processing Systems, Vol. 37 (2024), 50772-50804.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482417"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.322"},{"key":"e_1_3_2_1_52_1","volume-title":"When not to trust language models: Investigating effectiveness of parametric and non-parametric memories. arXiv preprint arXiv:2212.10511","author":"Mallen Alex","year":"2022","unstructured":"Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, and Hannaneh Hajishirzi. 2022. When not to trust language models: Investigating effectiveness of parametric and non-parametric memories. arXiv preprint arXiv:2212.10511 (2022)."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"crossref","unstructured":"Long Ouyang Jeffrey Wu Xu Jiang Diogo Almeida Carroll Wainwright Pamela Mishkin Chong Zhang Sandhini Agarwal Katarina Slama Alex Ray et al. 2022. Training language models to follow instructions with human feedback. Advances in neural information processing systems Vol. 35 (2022) 27730-27744.","DOI":"10.52202\/068431-2011"},{"key":"e_1_3_2_1_54_1","volume-title":"Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, et al.","author":"Roziere Baptiste","year":"2023","unstructured":"Baptiste Roziere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, et al., 2023. Code llama: Open foundation models for code. arXiv preprint arXiv:2308.12950 (2023)."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608845"},{"key":"e_1_3_2_1_56_1","volume-title":"Replug: Retrieval-augmented black-box language models. arXiv preprint arXiv:2301.12652","author":"Shi Weijia","year":"2023","unstructured":"Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, and Wen-tau Yih. 2023. Replug: Retrieval-augmented black-box language models. arXiv preprint arXiv:2301.12652 (2023)."},{"key":"e_1_3_2_1_57_1","volume-title":"Retrieval augmentation reduces hallucination in conversation. arXiv preprint arXiv:2104.07567","author":"Shuster Kurt","year":"2021","unstructured":"Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston. 2021. Retrieval augmentation reduces hallucination in conversation. arXiv preprint arXiv:2104.07567 (2021)."},{"key":"e_1_3_2_1_58_1","first-page":"565","article-title":"Personalized top-n sequential recommendation via convolutional sequence embedding","author":"Tang Jiaxi","year":"2018","unstructured":"Jiaxi Tang and Ke Wang. 2018. Personalized top-n sequential recommendation via convolutional sequence embedding. In WSDM. 565-573.","journal-title":"WSDM."},{"key":"e_1_3_2_1_59_1","volume-title":"Qwen2 technical report. arXiv preprint arXiv:2407.10671","author":"Team Qwen","year":"2024","unstructured":"Qwen Team. 2024. Qwen2 technical report. arXiv preprint arXiv:2407.10671, Vol. 2 (2024)."},{"key":"e_1_3_2_1_60_1","volume-title":"Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, et al.","author":"Thoppilan Romal","year":"2022","unstructured":"Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, et al., 2022. Lamda: Language models for dialog applications. arXiv preprint arXiv:2201.08239 (2022)."},{"key":"e_1_3_2_1_61_1","unstructured":"Hugo Touvron Louis Martin Kevin Stone Peter Albert Amjad Almahairi Yasmine Babaei Nikolay Bashlykov Soumya Batra Prajjwal Bhargava Shruti Bhosale et al. 2023. Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288 (2023)."},{"key":"e_1_3_2_1_62_1","volume-title":"Query2doc: Query Expansion with Large Language Models. arXiv:2303.07678","author":"Wang Liang","year":"2023","unstructured":"Liang Wang, Nan Yang, and Furu Wei. 2023a. Query2doc: Query Expansion with Large Language Models. arXiv:2303.07678 (2023)."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3698590","article-title":"Knowledge editing for large language models: A survey","volume":"57","author":"Wang Song","year":"2024","unstructured":"Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, and Jundong Li. 2024. Knowledge editing for large language models: A survey. Comput. Surveys, Vol. 57, 3 (2024), 1-37.","journal-title":"Comput. Surveys"},{"key":"e_1_3_2_1_64_1","volume-title":"Knowledgpt: Enhancing large language models with retrieval and storage access on knowledge bases. arXiv preprint arXiv:2308.11761","author":"Wang Xintao","year":"2023","unstructured":"Xintao Wang, Qianwen Yang, Yongting Qiu, Jiaqing Liang, Qianyu He, Zhouhong Gu, Yanghua Xiao, and Wei Wang. 2023b. Knowledgpt: Enhancing large language models with retrieval and storage access on knowledge bases. arXiv preprint arXiv:2308.11761 (2023)."},{"key":"e_1_3_2_1_65_1","unstructured":"Shitao Xiao Zheng Liu Peitian Zhang and Niklas Muennighoff. 2023. C-Pack: Packaged Resources To Advance General Chinese Embedding. arXiv:2309.07597 [cs.CL]"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657878"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"crossref","unstructured":"Zhengyi Yang et al. 2023. A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. (2023).","DOI":"10.1145\/3539618.3591624"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.acl-long.830"},{"key":"e_1_3_2_1_69_1","volume-title":"International Conference on Learning Representations (ICLR).","author":"Yao Shunyu","year":"2023","unstructured":"Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023. React: Synergizing reasoning and acting in language models. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_70_1","volume-title":"Inference scaling for long-context retrieval augmented generation. arXiv preprint arXiv:2410.04343","author":"Yue Zhenrui","year":"2024","unstructured":"Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, and Michael Bendersky. 2024. Inference scaling for long-context retrieval augmented generation. arXiv preprint arXiv:2410.04343 (2024)."},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608860"},{"key":"e_1_3_2_1_72_1","volume-title":"Retrieve anything to augment large language models. arXiv preprint arXiv:2310.07554","author":"Zhang Peitian","year":"2023","unstructured":"Peitian Zhang, Shitao Xiao, Zheng Liu, Zhicheng Dou, and Jian-Yun Nie. 2023b. Retrieve anything to augment large language models. arXiv preprint arXiv:2310.07554 (2023)."},{"key":"e_1_3_2_1_73_1","volume-title":"Collm: Integrating collaborative embeddings into large language models for recommendation","author":"Zhang Yang","year":"2025","unstructured":"Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, and Xiangnan He. 2025. Collm: Integrating collaborative embeddings into large language models for recommendation. IEEE Transactions on Knowledge and Data Engineering (2025)."},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591752"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE60146.2024.00118"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/1060745.1060754"}],"event":{"name":"WWW '26: The ACM Web Conference 2026","location":"Dubai United Arab Emirates","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2026"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3774904.3792364","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T15:38:04Z","timestamp":1780673884000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792364"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":76,"alternative-id":["10.1145\/3774904.3792364","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792364","relation":{},"subject":[],"published":{"date-parts":[[2026,4,12]]},"assertion":[{"value":"2026-04-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}