
GINopic, a neural topic model that leverages a graph isomorphism network to enhance the representation of word correlations in documents, outperforms existing topic models in terms of topic coherence, diversity, and downstream task performance.


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GINopic: A Graph Isomorphism Network-based Neural Topic Model for Capturing Word Correlations


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Large Language Models (LLMs) can enhance topic modeling by providing dynamic and interactive representations, making it more accessible and comprehensive.


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GPTopic: Dynamic and Interactive Topic Representations



The author introduces GPTopic, a software package that utilizes Large Language Models to create dynamic and interactive topic representations, aiming to make topic modeling more accessible and comprehensive.


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GPTopic: Dynamic and Interactive Topic Representations Unveiled
