The paper evaluates four LLMs as text augmenters and reports GPT-3.5 Turbo as the best, and that combining augmentation with GPT topic labels increases BERTopic's discovered topics from 5 to 20 with zero overlap.
Enhancing BERTopic with Pre-Clustered Knowledge: Reducing Feature Sparsity in Short Text Topic Modeling,
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Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis
The paper evaluates four LLMs as text augmenters and reports GPT-3.5 Turbo as the best, and that combining augmentation with GPT topic labels increases BERTopic's discovered topics from 5 to 20 with zero overlap.