cs.AI updates on arXiv.org 11月05日 13:24
晚期交互检索方法研讨会
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本文介绍了晚期交互检索方法,特别是ColBERT的先驱作用,以及其在跨领域应用中的优势与挑战。研讨会旨在促进研究者与实践者之间的交流与合作。

arXiv:2511.00444v1 Announce Type: cross 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 late interaction can be discussed, with a focus on early research explorations, real-world outcomes, and negative or puzzling results to be freely shared and discussed. The aim of LIR is to provide a highly-interactive environment for researchers from various backgrounds and practitioners to freely discuss their experience, fostering further collaboration.

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晚期交互检索 ColBERT 跨领域应用 研讨会 研究者交流
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