Papers by Joo-kyung Kim

1 papers
Cluster-Guided Label Generation in Extreme Multi-Label Classification (2023.eacl-main)

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Challenge: Existing classification-based models are poorly per-form for tail labels and ignore semantic relations among labels.
Approach: They propose to guide label generation using label cluster information to hierarchically generate lower-level labels.
Outcome: The proposed model outperforms classification and generation baselines on tail labels and improves in four popular XMC benchmarks.

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