{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:10:44Z","timestamp":1774311044999,"version":"3.50.1"},"publisher-location":"Cham","reference-count":43,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032213235","type":"print"},{"value":"9783032213242","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-21324-2_11","type":"book-chapter","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T08:39:30Z","timestamp":1774255170000},"page":"158-168","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LIR: The First Workshop on\u00a0Late Interaction and\u00a0Multi Vector Retrieval @ ECIR 2026"],"prefix":"10.1007","author":[{"given":"Benjamin","family":"Clavi\u00e9","sequence":"first","affiliation":[]},{"given":"Xianming","family":"Li","sequence":"additional","affiliation":[]},{"given":"Antoine","family":"Chaffin","sequence":"additional","affiliation":[]},{"given":"Omar","family":"Khattab","sequence":"additional","affiliation":[]},{"given":"Tom","family":"Aarsen","sequence":"additional","affiliation":[]},{"given":"Manuel","family":"Faysse","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,24]]},"reference":[{"key":"11_CR1","unstructured":"BigScienceWorkshop, Scao, T.L., et\u00a0al.: Bloom: a 176b-parameter open-access multilingual language model. arXiv preprint arXiv:2211.05100 (2022)"},{"key":"11_CR2","unstructured":"Chaffin, A.: Gte-moderncolbert (2025). https:\/\/huggingface.co\/lightonai\/GTE-ModernColBERT-v1"},{"key":"11_CR3","unstructured":"Chaffin, A.: Reason-moderncolbert (2025). https:\/\/huggingface.co\/lightonai\/Reason-ModernColBERT"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Chaffin, A., Sourty, R.: Pylate: Flexible training and retrieval for late interaction models. arXiv preprint arXiv:2508.03555 (Accepted at CIKM 2025, to be published) (2025)","DOI":"10.1145\/3746252.3761608"},{"key":"11_CR5","unstructured":"Chen, Z., et\u00a0al.: Browsecomp-plus: a more fair and transparent evaluation benchmark of deep-research agent. arXiv preprint arXiv:2508.06600 (2025)"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Clavi\u00e9, B.: Jacolbertv2. 5: Optimising multi-vector retrievers to create state-of-the-art Japanese retrievers with constrained resources. J. Natural Lang. Process. 32(1), 176\u2013218 (2025)","DOI":"10.5715\/jnlp.32.176"},{"key":"11_CR7","unstructured":"Clavi\u00e9, B.: Ragatouille: Easily use and train state-of-the-art late-interaction retrieval methods (ColBERT) in any rag pipeline (2025). https:\/\/github.com\/AnswerDotAI\/RAGatouille, version 0.0.9 (2025-02-10)"},{"key":"11_CR8","unstructured":"Clavi\u00e9, B., Chaffin, A., Adams, G.: Reducing the footprint of multi-vector retrieval with minimal performance impact via token pooling. arXiv preprint arXiv:2409.14683 (2024)"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Conti, M., et al.: Context is gold to find the gold passage: Evaluating and training contextual document embeddings. arXiv preprint arXiv:2505.24782 (2025)","DOI":"10.18653\/v1\/2025.emnlp-main.1150"},{"key":"11_CR10","unstructured":"Faysse, M., et al.: Colpali: efficient document retrieval with vision language models. In: ICLR (2025)"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Formal, T., Piwowarski, B., Clinchant, S.: Splade: Sparse lexical and expansion model for first stage ranking. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 2288\u20132292 (2021)","DOI":"10.1145\/3404835.3463098"},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Giacalone, B., Paiement, G., Tucker, Q., Zanibbi, R.: Beneath the [MASK]: an analysis of structural query tokens in ColBERT. In: European Conference on Information Retrieval, pp. 431\u2013439. Springer (2024)","DOI":"10.1007\/978-3-031-56063-7_35"},{"key":"11_CR13","unstructured":"Jain, H., et al.: Efficient document ranking with learnable late interactions. In: 2nd Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ ICML 2024) (2024)"},{"key":"11_CR14","first-page":"101042","volume":"37","author":"R Jayaram","year":"2024","unstructured":"Jayaram, R., Dhulipala, L., Hadian, M., Lee, J.D., Mirrokni, V.: Muvera: multi-vector retrieval via fixed dimensional encoding. Adv. Neural. Inf. Process. Syst. 37, 101042\u2013101073 (2024)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Karpukhin, V., et al.: Dense passage retrieval for open-domain question answering. In: EMNLP (1), pp. 6769\u20136781 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"11_CR16","unstructured":"Khattab, O., et\u00a0al.: DSPy: compiling declarative language model calls into state-of-the-art pipelines. In: The Twelfth International Conference on Learning Representations (2024)"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Khattab, O., Zaharia, M.: ColBERT: efficient and effective passage search via contextualized late interaction over BERT. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 39\u201348 (2020)","DOI":"10.1145\/3397271.3401075"},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Killingback, J., Zeng, H., Zamani, H.: Hypencoder: hypernetworks for information retrieval. In: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 2372\u20132383 (2025)","DOI":"10.1145\/3726302.3729983"},{"key":"11_CR19","first-page":"15384","volume":"36","author":"J Lee","year":"2023","unstructured":"Lee, J., et al.: Rethinking the role of token retrieval in multi-vector retrieval. Adv. Neural. Inf. Process. Syst. 36, 15384\u201315405 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"Li, X., Li, J.: Aoe: Angle-optimized embeddings for semantic textual similarity. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1825\u20131839 (2024)","DOI":"10.18653\/v1\/2024.acl-long.101"},{"key":"11_CR21","unstructured":"Li, X., Li, Z., Li, J., Xie, H., Li, Q.: Ese: Espresso sentence embeddings. In: The Thirteenth International Conference on Learning Representations, ICLR2025 (2025)"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Liu, Y.A., et al.: Robust-ir@ sigir 2025: the first workshop on robust information retrieval. In: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 4142\u20134145 (2025)","DOI":"10.1145\/3726302.3730355"},{"key":"11_CR23","unstructured":"Louis, A., Saxena, V.K., van Dijck, G., Spanakis, G.: ColBERT-xm: a modular multi-vector representation model for zero-shot multilingual information retrieval. In: Proceedings of the 31st International Conference on Computational Linguistics, pp. 4370\u20134383 (2025)"},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"Ma, Y., et\u00a0al.: Towards storage-efficient visual document retrieval: An empirical study on reducing patch-level embeddings. arXiv preprint arXiv:2506.04997 (2025)","DOI":"10.18653\/v1\/2025.findings-acl.1003"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"MacAvaney, S., Mallia, A., Tonellotto, N.: Efficient constant-space multi-vector retrieval. In: European Conference on Information Retrieval, pp. 237\u2013245. Springer (2025)","DOI":"10.1007\/978-3-031-88714-7_22"},{"key":"11_CR26","doi-asserted-by":"crossref","unstructured":"Macdonald, C., Tonellotto, N., MacAvaney, S., Ounis, I.: Pyterrier: Declarative experimentation in python from bm25 to dense retrieval. In: Proceedings of the 30th ACM International Conference on Information and Knowledge Management, pp. 4526\u20134533 (2021)","DOI":"10.1145\/3459637.3482013"},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Nair, S., et al.: Transfer learning approaches for building cross-language dense retrieval models. In: Proceedings of the 44th European Conference on Information Retrieval (ECIR) (2022). https:\/\/arxiv.org\/abs\/2201.08471","DOI":"10.1007\/978-3-030-99736-6_26"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Nogueira, R., Jiang, Z., Pradeep, R., Lin, J.: Document ranking with a pretrained sequence-to-sequence model. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 708\u2013718 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.63"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Ounis, I., et al.: Terrier information retrieval platform. In: European Conference on Information Retrieval, pp. 517\u2013519. Springer (2005)","DOI":"10.1007\/978-3-540-31865-1_37"},{"key":"11_CR30","doi-asserted-by":"crossref","unstructured":"Reddy, A., et al.: Video-ColBERT: contextualized late interaction for text-to-video retrieval. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 19691\u201319701 (2025)","DOI":"10.1109\/CVPR52734.2025.01834"},{"key":"11_CR31","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: Sentence embeddings using Siamese BERT-networks. arXiv preprint arXiv:1908.10084 (2019)","DOI":"10.18653\/v1\/D19-1410"},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Santhanam, K., Khattab, O., Potts, C., Zaharia, M.: Plaid: an efficient engine for late interaction retrieval. In: Proceedings of the 31st ACM International Conference on Information and Knowledge Management, pp. 1747\u20131756 (2022)","DOI":"10.1145\/3511808.3557325"},{"key":"11_CR33","doi-asserted-by":"crossref","unstructured":"Santhanam, K., Khattab, O., Saad-Falcon, J., Potts, C., Zaharia, M.: Colbertv2: effective and efficient retrieval via lightweight late interaction. In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 3715\u20133734 (2022)","DOI":"10.18653\/v1\/2022.naacl-main.272"},{"key":"11_CR34","doi-asserted-by":"crossref","unstructured":"Scheerer, J.L., Zaharia, M., Potts, C., Alonso, G., Khattab, O.: Warp: an efficient engine for multi-vector retrieval. In: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 2504\u20132512 (2025)","DOI":"10.1145\/3726302.3729904"},{"key":"11_CR35","unstructured":"Shao, R., et\u00a0al.: ReasonIR: Training retrievers for reasoning tasks. arXiv preprint arXiv:2504.20595 (2025)"},{"key":"11_CR36","unstructured":"Team, N.: Nomic embed multimodal: Interleaved text, image, and screenshots for visual document retrieval (2025). https:\/\/nomic.ai\/blog\/posts\/nomic-embed-multimodal"},{"key":"11_CR37","unstructured":"Veneroso, J., et al.: Crisp: Clustering multi-vector representations for denoising and pruning. arXiv preprint arXiv:2505.11471 (2025)"},{"key":"11_CR38","unstructured":"Wang, L., et al.: Text embeddings by weakly-supervised contrastive pre-training. arXiv preprint arXiv:2212.03533 (2022)"},{"key":"11_CR39","doi-asserted-by":"crossref","unstructured":"Warner, B., et al.: Smarter, better, faster, longer: a modern bidirectional encoder for fast, memory efficient, and long context finetuning and inference. In: Che, W., Nabende, J., Shutova, E., Pilehvar, M.T. (eds.) Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025) (Volume 1: Long Papers), pp. 2526\u20132547. Association for Computational Linguistics, Vienna, Austria (2025)","DOI":"10.18653\/v1\/2025.acl-long.127"},{"key":"11_CR40","unstructured":"Weller, O., Boratko, M., Naim, I., Lee, J.: On the theoretical limitations of embedding-based retrieval (2025). https:\/\/arxiv.org\/abs\/2508.21038"},{"key":"11_CR41","doi-asserted-by":"crossref","unstructured":"Weller, O., et al: FollowIR: Evaluating and teaching information retrieval models to follow instructions. In: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 11926\u201311942 (2025)","DOI":"10.18653\/v1\/2025.naacl-long.597"},{"key":"11_CR42","unstructured":"Wolf, T.: Most liked and most downloaded open-source ai models from 2022 to 2024. https:\/\/huggingface.co\/posts\/thomwolf\/250854638539377 (Dec 2024), hugging Face post, posted 4 December 2024"},{"key":"11_CR43","doi-asserted-by":"crossref","unstructured":"Xiao, H., Wang, B., Jha, R.: Jina-ColBERT-v2: a general-purpose multilingual late interaction retriever. In: Proceedings of the Fourth Workshop on Multilingual Representation Learning (MRL 2024), pp. 159\u2013166 (2024)","DOI":"10.18653\/v1\/2024.mrl-1.11"}],"container-title":["Lecture Notes in Computer Science","Advances in Information Retrieval"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-21324-2_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T23:16:46Z","timestamp":1774307806000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-21324-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032213235","9783032213242"],"references-count":43,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-21324-2_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"24 March 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Benjamin Clavi\u00e9 and Xianming Li are employed at Mixedbread, a company whose work is partially focusing on scaling and selling commercial solutions leveraging subsets of late interaction techniques. The authors have no other competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ECIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Information Retrieval","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Delft","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 March 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 April 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"48","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecir2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecir2026.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}