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LongEval: Longitudinal Evaluation of Model Performance at CLEF 2023
- Source :
- Lecture Notes in Computer Science ISBN: 9783031282409, ECIR 2023: Advances in Information Retrieval, European Conference on Information Retrieval, European Conference on Information Retrieval, Apr 2023, Dublin, Ireland. pp.499-505, ⟨10.1007/978-3-031-28241-6_58⟩
- Publication Year :
- 2023
- Publisher :
- Springer Nature Switzerland, 2023.
-
Abstract
- International audience; 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.
Details
- ISBN :
- 978-3-031-28240-9
- ISBNs :
- 9783031282409
- Database :
- OpenAIRE
- Journal :
- Lecture Notes in Computer Science ISBN: 9783031282409, ECIR 2023: Advances in Information Retrieval, European Conference on Information Retrieval, European Conference on Information Retrieval, Apr 2023, Dublin, Ireland. pp.499-505, ⟨10.1007/978-3-031-28241-6_58⟩
- Accession number :
- edsair.doi.dedup.....94f8c74f3d421c3f7797e204b8a0b800
- Full Text :
- https://doi.org/10.1007/978-3-031-28241-6_58