Benchmarking Neural Topic Models: An Empirical Study

Anthology ID:: 2021.findings-acl.382
Volume:: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:: August
Year:: 2021
Address:: Online
Editors:: Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venue:: Findings
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 4363–4368
Language:
URL:: https://aclanthology.org/2021.findings-acl.382
DOI:: 10.18653/v1/2021.findings-acl.382
Bibkey:
Cite (ACL):: Thanh-Nam Doan and Tuan-Anh Hoang. 2021. Benchmarking Neural Topic Models: An Empirical Study. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 4363–4368, Online. Association for Computational Linguistics.
Cite (Informal):: Benchmarking Neural Topic Models: An Empirical Study (Doan & Hoang, Findings 2021)
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