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Contrastive Learning for Neural Topic Model
[article]
2021
arXiv
pre-print
Recent empirical studies show that adversarial topic models (ATM) can successfully capture semantic patterns of the document by differentiating a document with another dissimilar sample. However, utilizing that discriminative-generative architecture has two important drawbacks: (1) the architecture does not relate similar documents, which has the same document-word distribution of salient words; (2) it restricts the ability to integrate external information, such as sentiments of the document,
arXiv:2110.12764v1
fatcat:2oz4s2hfnvdjbpne6inqclpufa