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News/Model-Agnostic Meta Learning for Class Imbalance Adaptation
arxiv
PublishedApril 22, 2026 at 4:00 AM
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Model-Agnostic Meta Learning for Class Imbalance Adaptation

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Publisher summary· verbatim

arXiv:2604.18759v1 Announce Type: new Abstract: Class imbalance is a widespread challenge in NLP tasks, significantly hindering robust performance across diverse domains and applications. We introduce Hardness-Aware Meta-Resample (HAMR), a unified framework that adaptively addresses both class imbal

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    Hardness-Aware Meta-Resample (HAMR)
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#nlp#class-imbalance#resampling

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Mentioned models
01
  • 01
    Hardness-Aware Meta-Resample (HAMR)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#nlp#class-imbalance#resampling

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