January 2017
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43 Reads
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28 Citations
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Publications (1)
Citations (1)
... This work has explored use of document metadata (Card et al., 2018), seed words per topic (Jagarlamudi et al., 2012), and constraints to supervise and refine latent topics (Hu et al., 2011). However, generative topic models prove challenging to scale to large corpora (Lund et al., 2017), are influenced by document lengths (Hong and Davison, 2010), and are limited in their ability to leverage performant pre-trained language models (Hoyle et al., 2022). While an emerging body of work has effectively leveraged pre-trained language models for unsupervised topic modeling (Pham et al., 2024;Thompson and Mimno, 2020) exploration of contemporary pretrained models for interactive topic modeling has been limited. ...
- Citing Conference Paper
January 2017