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LongEval: Longitudinal Evaluation of Model Performance at CLEF 2023

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AS248VU9A" target="_blank" >RIV/00216208:11320/23:S248VU9A - isvavai.cz</a>

  • Result on the web

    <a href="https://www.webofscience.com/wos/woscc/summary/06ff7b3b-7e51-4590-a737-664e7ff2151f-bb8928e9/relevance/1" target="_blank" >https://www.webofscience.com/wos/woscc/summary/06ff7b3b-7e51-4590-a737-664e7ff2151f-bb8928e9/relevance/1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-28241-6_58" target="_blank" >10.1007/978-3-031-28241-6_58</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    LongEval: Longitudinal Evaluation of Model Performance at CLEF 2023

  • Original language description

    "In this paper, we describe the plans for the first LongEval CLEF 2023 shared task dedicated to evaluating the temporal persistence of Information Retrieval (IR) systems and Text Classifiers. The task is motivated by recent research showing that the performance of these models drops as the test data becomes more distant, with respect to time, from the training data. LongEval differs from traditional shared IR and classification tasks by giving special consideration to evaluating models aiming to mitigate performance drop over time. We envisage that this task will draw attention from the IR community and NLP researchers to the problem of temporal persistence of models, what enables or prevents it, potential solutions and their limitations."

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    "ADVANCES IN INFORMATION RETRIEVAL, ECIR 2023, PT III"

  • ISBN

    978-3-031-28240-9

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    499-505

  • Publisher name

    Springer International Publishing Ag

  • Place of publication

    Cham

  • Event location

    Cham

  • Event date

    Jan 1, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000995495200058