Cross-encoder Re-ranking

Cross-Encoder Re-Ranking is a passage retrieval method that, as a member of the re-ranking models in semantic search, employs a bidirectional interaction architecture to jointly encode query-passage pairs and produce a refined relevance score through deep semantic fusion.

6

Publications

599

Citations

30

Authors

8

Institutions

Publications per year

2017–2026

6

Authors

30

  1. LW
    Ledell Wu

    Beijing Academy of Artificial Intelligence, China

    2 publications · 358 citations

    2

    h-index

  2. FP
    Fabio Petroni

    Meta (Israel), Israel

    2 publications · 358 citations

    2

    h-index

  3. SR
    Sebastian Riedel

    University College London, United Kingdom

    2 publications · 358 citations

    2

    h-index

  4. MJ
    Martin Josifoski

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 358 citations

    2

    h-index

  5. LZ
    Luke Zettlemoyer

    University of Washington, United States

    2 publications · 358 citations

    2

    h-index

1–5 of 30

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 100 citations

    3

    h-index

  2. Frontiers in Public Health

    1 publications · 22 citations

1–2