SPIRIT: Structural Entropy Guided Prefix Tuning for Hierarchical Text Classification

SPIRIT: Structural Entropy Guided Prefix Tuning for Hierarchical Text Classification

Hierarchical text classification (HTC) is a challenging task that requires classifiers to solve a series of multi-label subtasks considering hierarchical dependencies among labels. Recent studies have introduced prompt tuning to create closer connections between the language model (LM) and the compl...

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Bibliografiska uppgifter
Huvudupphovsmän: He Zhu, Jinxiang Xia, Ruomei Liu, Bowen Deng
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2025-01-01
Serie:Entropy
Ämnen:
information theory
structural entropy
representation learning
Länkar:https://www.mdpi.com/1099-4300/27/2/128

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https://www.mdpi.com/1099-4300/27/2/128

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