Papers with topic issue

1 papers
Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusion (2024.findings-acl)

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Challenge: Existing dynamic topic models lack the ability to reveal the evolution of topics . Existing models suffer from repetitive topic and unassociated topic issues .
Approach: They propose a new evolution-tracking contrastive learning method that builds the similarity relations among dynamic topics and an unassociated word exclusion method to avoid unassociated topics.
Outcome: The proposed model outperforms state-of-the-art models on downstream tasks and is robust to evolution intensities.

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