LIR: The First Workshop on Late Interaction and Multi Vector Retrieval @ ECIR 2026
Benjamin Clavi\'e, Xianming Li, Antoine Chaffin, Omar Khattab, Tom Aarsen, Manuel Faysse, Jing Li

TL;DR
This paper introduces the LIR workshop focusing on late interaction and multi-vector retrieval methods, highlighting recent advances, challenges, and fostering collaboration among researchers and practitioners in the field.
Contribution
It presents the first workshop dedicated to late interaction retrieval, emphasizing the importance of interdisciplinary discussion and sharing of early research, real-world outcomes, and challenges.
Findings
Late interaction methods show strong generalisation and robustness.
Recent advances address efficiency and usability challenges.
The workshop fosters collaboration across communities.
Abstract
Late interaction retrieval methods, pioneered by ColBERT, have emerged as a powerful alternative to single-vector neural IR. By leveraging fine-grained, token-level representations, they have been demonstrated to deliver strong generalisation and robustness, particularly in out-of-domain settings. They have recently been shown to be particularly well-suited for novel use cases, such as reasoning-based or cross-modality retrieval. At the same time, these models pose significant challenges of efficiency, usability, and integrations into fully fledged systems; as well as the natural difficulties encountered while researching novel application domains. Recent years have seen rapid advances across many of these areas, but research efforts remain fragmented across communities and frequently exclude practitioners. The purpose of this workshop is to create an environment where all aspects of…
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Taxonomy
TopicsTopic Modeling · Multimodal Machine Learning Applications · Information Retrieval and Search Behavior
