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%0 Conference Proceedings
%T Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
%A Ginzburg, Dvir
%A Malkiel, Itzik
%A Barkan, Oren
%A Caciularu, Avi
%A Koenigstein, Noam
%Y Zong, Chengqing
%Y Xia, Fei
%Y Li, Wenjie
%Y Navigli, Roberto
%S Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F ginzburg-etal-2021-self
%R 10.18653/v1/2021.findings-acl.272
%U https://aclanthology.org/2021.findings-acl.272
%U https://doi.org/10.18653/v1/2021.findings-acl.272
%P 3088-3098

Markdown (Informal)

[Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference](https://aclanthology.org/2021.findings-acl.272) (Ginzburg et al., Findings 2021)

• Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference (Ginzburg et al., Findings 2021)

ACL

• Dvir Ginzburg, Itzik Malkiel, Oren Barkan, Avi Caciularu, and Noam Koenigstein. 2021. Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3088–3098, Online. Association for Computational Linguistics.