{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T22:21:31Z","timestamp":1791498091604,"version":"4.3.4"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,7,20]],"date-time":"2025-07-20T00:00:00Z","timestamp":1752969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,20]]},"DOI":"10.1145\/3690624.3709194","type":"proceedings-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T18:42:22Z","timestamp":1743792142000},"page":"589-600","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["PipeRAG: Fast Retrieval-Augmented Generation via Adaptive Pipeline Parallelism"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3895-7943","authenticated-orcid":false,"given":"Wenqi","family":"Jiang","sequence":"first","affiliation":[{"name":"ETH Zurich, Zurich, Zurich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7866-4611","authenticated-orcid":false,"given":"Shuai","family":"Zhang","sequence":"additional","affiliation":[{"name":"Amazon Web Services, Santa Clara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9567-7062","authenticated-orcid":false,"given":"Boran","family":"Han","sequence":"additional","affiliation":[{"name":"Amazon Web Services, Santa Clara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2133-7943","authenticated-orcid":false,"given":"Jie","family":"Wang","sequence":"additional","affiliation":[{"name":"Meta, Santa Clara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0291-7184","authenticated-orcid":false,"given":"Bernie","family":"Wang","sequence":"additional","affiliation":[{"name":"Amazon Web Services, Santa Clara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2414-2759","authenticated-orcid":false,"given":"Tim","family":"Kraska","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,7,20]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"The wikipedia dataset. https:\/\/www.tensorflow.org\/datasets\/community_catalog\/ huggingface\/wikipedia."},{"key":"e_1_3_2_2_2_1","volume-title":"Longformer: The long-document transformer. arXiv preprint arXiv:2004.05150","author":"Beltagy Iz","year":"2020","unstructured":"Iz Beltagy, MatthewE Peters, and Arman Cohan. Longformer: The long-document transformer. arXiv preprint arXiv:2004.05150, 2020."},{"key":"e_1_3_2_2_3_1","first-page":"2206","volume-title":"International conference on machine learning","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. Improving language models by retrieving from trillions of tokens. In International conference on machine learning, pages 2206--2240. PMLR, 2022."},{"key":"e_1_3_2_2_4_1","volume-title":"Language models are few-shot learners. Advances in neural information processing systems, 33:1877--1901","author":"Brown Tom","year":"2020","unstructured":"Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda 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_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331303"},{"key":"e_1_3_2_2_6_1","volume-title":"Documenting large webtext corpora: A case study on the colossal clean crawled corpus. arXiv preprint arXiv:2104.08758","author":"Dodge Jesse","year":"2021","unstructured":"Jesse Dodge, Maarten Sap, Ana Marasovi\u0107, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Margaret Mitchell, and Matt Gardner. Documenting large webtext corpora: A case study on the colossal clean crawled corpus. arXiv preprint arXiv:2104.08758, 2021."},{"key":"e_1_3_2_2_7_1","volume-title":"Surface-based retrieval reduces perplexity of retrieval-augmented language models. arXiv preprint arXiv:2305.16243","author":"Doostmohammadi Ehsan","year":"2023","unstructured":"Ehsan Doostmohammadi, Tobias Norlund, Marco Kuhlmann, and Richard Johansson. Surface-based retrieval reduces perplexity of retrieval-augmented language models. arXiv preprint arXiv:2305.16243, 2023."},{"key":"e_1_3_2_2_8_1","first-page":"5547","volume-title":"International Conference on Machine Learning","author":"Du Nan","year":"2022","unstructured":"Nan Du, Yanping Huang, Andrew M Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, et al. Glam: Efficient scaling of language models with mixture-of-experts. In International Conference on Machine Learning, pages 5547--5569. PMLR, 2022."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/3586589.3586709"},{"key":"e_1_3_2_2_10_1","volume-title":"Gptq: Accurate post-training quantization for generative pre-trained transformers. arXiv preprint arXiv:2210.17323","author":"Frantar Elias","year":"2022","unstructured":"Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh. Gptq: Accurate post-training quantization for generative pre-trained transformers. arXiv preprint arXiv:2210.17323, 2022."},{"key":"e_1_3_2_2_11_1","first-page":"3929","volume-title":"International conference on machine learning","author":"Guu Kelvin","year":"2020","unstructured":"Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. Retrieval augmented language model pre-training. In International conference on machine learning, pages 3929--3938. PMLR, 2020."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505665"},{"key":"e_1_3_2_2_13_1","volume-title":"Leveraging passage retrieval with generative models for open domain question answering. arXiv preprint arXiv:2007.01282","author":"Izacard Gautier","year":"2020","unstructured":"Gautier Izacard and Edouard Grave. Leveraging passage retrieval with generative models for open domain question answering. arXiv preprint arXiv:2007.01282, 2020."},{"key":"e_1_3_2_2_14_1","volume-title":"Few-shot learning with retrieval augmented language models. arXiv preprint arXiv:2208.03299","author":"Izacard Gautier","year":"2022","unstructured":"Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. Few-shot learning with retrieval augmented language models. arXiv preprint arXiv:2208.03299, 2022."},{"key":"e_1_3_2_2_15_1","volume-title":"Product quantization for nearest neighbor search","author":"Jegou Herve","year":"2010","unstructured":"Herve Jegou, Matthijs Douze, and Cordelia Schmid. Product quantization for nearest neighbor search. IEEE transactions on pattern analysis and machine intelligence, 33(1):117--128, 2010."},{"key":"e_1_3_2_2_16_1","volume-title":"Accelerating graph-based vector search via delayed-synchronization traversal. arXiv preprint arXiv:2406.12385","author":"Jiang Wenqi","year":"2024","unstructured":"Wenqi Jiang, Hang Hu, Torsten Hoefler, and Gustavo Alonso. Accelerating graph-based vector search via delayed-synchronization traversal. arXiv preprint arXiv:2406.12385, 2024."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581784.3607045"},{"key":"e_1_3_2_2_18_1","volume-title":"Chameleon: a heterogeneous and disaggregated accelerator system for retrievalaugmented language models. arXiv preprint arXiv:2310.09949","author":"Jiang Wenqi","year":"2023","unstructured":"Wenqi Jiang, Marco Zeller, Roger Waleffe, Torsten Hoefler, and Gustavo Alonso. Chameleon: a heterogeneous and disaggregated accelerator system for retrievalaugmented language models. arXiv preprint arXiv:2310.09949, 2023."},{"key":"e_1_3_2_2_19_1","volume-title":"Active retrieval augmented generation. arXiv preprint arXiv:2305.06983","author":"Jiang Zhengbao","year":"2023","unstructured":"Zhengbao Jiang, Frank F Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, and Graham Neubig. Active retrieval augmented generation. arXiv preprint arXiv:2305.06983, 2023."},{"key":"e_1_3_2_2_20_1","volume-title":"Ragcache: Efficient knowledge caching for retrieval-augmented generation. arXiv preprint arXiv:2404.12457","author":"Jin Chao","year":"2024","unstructured":"Chao Jin, Zili Zhang, Xuanlin Jiang, Fangyue Liu, Xin Liu, Xuanzhe Liu, and Xin Jin. Ragcache: Efficient knowledge caching for retrieval-augmented generation. arXiv preprint arXiv:2404.12457, 2024."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_2_22_1","volume-title":"Dense passage retrieval for open-domain question answering. arXiv preprint arXiv:2004.04906","author":"Karpukhin Vladimir","year":"2020","unstructured":"Vladimir Karpukhin, Barlas O\u011fuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. Dense passage retrieval for open-domain question answering. arXiv preprint arXiv:2004.04906, 2020."},{"key":"e_1_3_2_2_23_1","volume-title":"Nearest neighbor machine translation. arXiv preprint arXiv:2010.00710","author":"Khandelwal Urvashi","year":"2020","unstructured":"Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. Nearest neighbor machine translation. arXiv preprint arXiv:2010.00710, 2020."},{"key":"e_1_3_2_2_24_1","volume-title":"Generalization through memorization: Nearest neighbor language models. arXiv preprint arXiv:1911.00172","author":"Khandelwal Urvashi","year":"2019","unstructured":"Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. Generalization through memorization: Nearest neighbor language models. arXiv preprint arXiv:1911.00172, 2019."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401075"},{"key":"e_1_3_2_2_26_1","volume-title":"Internet-augmented dialogue generation. arXiv preprint arXiv:2107.07566","author":"Komeili Mojtaba","year":"2021","unstructured":"Mojtaba Komeili, Kurt Shuster, and Jason Weston. Internet-augmented dialogue generation. arXiv preprint arXiv:2107.07566, 2021."},{"key":"e_1_3_2_2_27_1","first-page":"18470","article-title":"Pre-training via paraphrasing","volume":"33","author":"Lewis Mike","year":"2020","unstructured":"Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh, Armen Aghajanyan, Sida Wang, and Luke Zettlemoyer. Pre-training via paraphrasing. Advances in Neural Information Processing Systems, 33:18470--18481, 2020.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_28_1","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","volume":"33","author":"Lewis Patrick","year":"2020","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. Retrieval-augmented generation for knowledge-intensive nlp tasks. Advances in Neural Information Processing Systems, 33:9459--9474, 2020.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331317"},{"key":"e_1_3_2_2_30_1","volume-title":"Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs","author":"Malkov Yu A","year":"2018","unstructured":"Yu A Malkov and Dmitry A Yashunin. Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE transactions on pattern analysis and machine intelligence, 42(4):824--836, 2018."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2013.10.006"},{"key":"e_1_3_2_2_32_1","volume-title":"Fast nearest neighbor machine translation. arXiv preprint arXiv:2105.14528","author":"Meng Yuxian","year":"2021","unstructured":"Yuxian Meng, Xiaoya Li, Xiayu Zheng, Fei Wu, Xiaofei Sun, Tianwei Zhang, and Jiwei Li. Fast nearest neighbor machine translation. arXiv preprint arXiv:2105.14528, 2021."},{"key":"e_1_3_2_2_33_1","volume-title":"Passage re-ranking with bert. arXiv preprint arXiv:1901.04085","author":"Nogueira Rodrigo","year":"2019","unstructured":"Rodrigo Nogueira and Kyunghyun Cho. Passage re-ranking with bert. arXiv preprint arXiv:1901.04085, 2019."},{"key":"e_1_3_2_2_34_1","volume-title":"On the generalization ability of retrieval-enhanced transformers. arXiv preprint arXiv:2302.12128","author":"Norlund Tobias","year":"2023","unstructured":"Tobias Norlund, Ehsan Doostmohammadi, Richard Johansson, and Marco Kuhlmann. On the generalization ability of retrieval-enhanced transformers. arXiv preprint arXiv:2302.12128, 2023."},{"key":"e_1_3_2_2_35_1","volume-title":"Improving language understanding by generative pre-training","author":"Radford Alec","year":"2018","unstructured":"Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al. Improving language understanding by generative pre-training. 2018."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.5555\/3455716.3455856"},{"key":"e_1_3_2_2_37_1","volume-title":"In-context retrieval-augmented language models. arXiv preprint arXiv:2302.00083","author":"Ram Ori","year":"2023","unstructured":"Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, and Yoav Shoham. In-context retrieval-augmented language models. arXiv preprint arXiv:2302.00083, 2023."},{"key":"e_1_3_2_2_38_1","volume-title":"Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084","author":"Reimers Nils","year":"2019","unstructured":"Nils Reimers and Iryna Gurevych. Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084, 2019."},{"key":"e_1_3_2_2_39_1","volume-title":"End-to-end training of neural retrievers for open-domain question answering. arXiv preprint arXiv:2101.00408","author":"Sachan Devendra Singh","year":"2021","unstructured":"Devendra Singh Sachan, Mostofa Patwary, Mohammad Shoeybi, Neel Kant, Wei Ping, William L Hamilton, and Bryan Catanzaro. End-to-end training of neural retrievers for open-domain question answering. arXiv preprint arXiv:2101.00408, 2021."},{"key":"e_1_3_2_2_40_1","volume-title":"Colbertv2: Effective and efficient retrieval via lightweight late interaction. arXiv preprint arXiv:2112.01488","author":"Santhanam Keshav","year":"2021","unstructured":"Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, and Matei Zaharia. Colbertv2: Effective and efficient retrieval via lightweight late interaction. arXiv preprint arXiv:2112.01488, 2021."},{"key":"e_1_3_2_2_41_1","first-page":"1470","volume-title":"IEEE International Conference on","volume":"3","author":"Sivic Josef","year":"2003","unstructured":"Josef Sivic and Andrew Zisserman. Video google: A text retrieval approach to object matching in videos. In Computer Vision, IEEE International Conference on, volume 3, pages 1470--1470. IEEE Computer Society, 2003."},{"key":"e_1_3_2_2_42_1","volume-title":"Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions. arXiv preprint arXiv:2212.10509","author":"Trivedi Harsh","year":"2022","unstructured":"Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions. arXiv preprint arXiv:2212.10509, 2022."},{"key":"e_1_3_2_2_43_1","volume-title":"Attention is all you need. Advances in neural information processing systems, 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. Attention is all you need. Advances in neural information processing systems, 30, 2017."},{"key":"e_1_3_2_2_44_1","volume-title":"Knn-lm does not improve open-ended text generation. arXiv preprint arXiv:2305.14625","author":"Wang Shufan","year":"2023","unstructured":"Shufan Wang, Yixiao Song, Andrew Drozdov, Aparna Garimella, Varun Manjunatha, and Mohit Iyyer. Knn-lm does not improve open-ended text generation. arXiv preprint arXiv:2305.14625, 2023."},{"key":"e_1_3_2_2_45_1","volume-title":"Why do nearest neighbor language models work? arXiv preprint arXiv:2301.02828","author":"Xu Frank F","year":"2023","unstructured":"Frank F Xu, Uri Alon, and Graham Neubig. Why do nearest neighbor language models work? arXiv preprint arXiv:2301.02828, 2023."},{"key":"e_1_3_2_2_46_1","volume-title":"Phitchaya Mangpo Phothilimthana, and Zhihao Jia. Accelerating retrieval-augmented language model serving with speculation. arXiv preprint arXiv:2401.14021","author":"Zhang Zhihao","year":"2024","unstructured":"Zhihao Zhang, Alan Zhu, Lijie Yang, Yihua Xu, Lanting Li, Phitchaya Mangpo Phothilimthana, and Zhihao Jia. Accelerating retrieval-augmented language model serving with speculation. arXiv preprint arXiv:2401.14021, 2024."}],"event":{"name":"KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Toronto ON Canada","acronym":"KDD '25","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3690624.3709194","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3690624.3709194","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T15:33:16Z","timestamp":1755358396000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3690624.3709194"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,20]]},"references-count":46,"alternative-id":["10.1145\/3690624.3709194","10.1145\/3690624"],"URL":"https:\/\/doi.org\/10.1145\/3690624.3709194","relation":{},"subject":[],"published":{"date-parts":[[2025,7,20]]},"assertion":[{"value":"2025-07-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}