Cluster-Guided Label Generation in Extreme Multi-Label Classification

Taehee Jung, Joo Kyung Kim, Sungjin Lee, Dongyeop Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For extreme multi-label classification (XMC), existing classification-based models poorly perform for tail labels and often ignore the semantic relations among labels, like treating “Wikipedia” and “Wiki” as independent and separate labels. In this paper, we cast XMC as a generation task (XLGen), where we benefit from pre-trained text-to-text models. However, generating labels from the extremely large label space is challenging without any constraints or guidance. We, therefore, propose to guide label generation using label cluster information to hierarchically generate lower-level labels. We also find that frequency-based label ordering and using decoding ensemble methods are critical factors for the improvements in XLGen. XLGen with cluster guidance significantly outperforms the classification and generation baselines on tail labels, and also generally improves the overall performance in four popular XMC benchmarks. In human evaluation, we also find XLGen generates unseen but plausible labels. Our code is now available at https://github.com/alexa/xlgen-eacl-2023.

Original languageEnglish (US)
Title of host publicationEACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages1662-1677
Number of pages16
ISBN (Electronic)9781959429449
StatePublished - 2023
Event17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023 - Dubrovnik, Croatia
Duration: May 2 2023May 6 2023

Publication series

NameEACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

Conference

Conference17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023
Country/TerritoryCroatia
CityDubrovnik
Period5/2/235/6/23

Bibliographical note

Publisher Copyright:
© 2023 Association for Computational Linguistics.

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