Modeling Text-Label Alignment for Hierarchical Text Classification-Reference-Cited by-同舟云学术

Modeling Text-Label Alignment for Hierarchical Text Classification

Published:2024 Issue: Volume: Page:163-179
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:en
Short-container-title:

Author:

Kumar Ashish^ORCID,Toshniwal Durga^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-70365-2_10

Reference27 articles.

1. Aly, R., Remus, S., Biemann, C.: Hierarchical multi-label classification of text with capsule networks. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pp. 323–330. Association for Computational Linguistics, Florence, Italy, July 2019. https://doi.org/10.18653/v1/P19-2045. https://aclanthology.org/P19-2045

2. Chen, B., Huang, X., Xiao, L., Cai, Z., Jing, L.: Hyperbolic interaction model for hierarchical multi-label classification. Proc. AAAI Conf. Artif. Intell. 34(05), 7496–7503 (2020). https://doi.org/10.1609/aaai.v34i05.6247. https://ojs.aaai.org/index.php/AAAI/article/view/6247

3. Chen, H., Ma, Q., Lin, Z., Yan, J.: Hierarchy-aware label semantics matching network for hierarchical text classification. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 4370–4379. Association for Computational Linguistics, August 2021. https://doi.org/10.18653/v1/2021.acl-long.337. https://aclanthology.org/2021.acl-long.337

4. Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: Proceedings of the 37th International Conference on Machine Learning, ICML 2020. JMLR.org (2020)

5. Chen, Z., et al.: Graph propagation transformer for graph representation learning. In: Elkind, E. (ed.) Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23, pp. 3559–3567. International Joint Conferences on Artificial Intelligence Organization (2023). https://doi.org/10.24963/ijcai.2023/396