GloCOM: A Short Text Neural Topic Model via Global Clustering Context (2025.naacl-long)
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| Challenge: | Existing neural topic models often overlook uncovering hidden topics from short texts due to data sparsity, poor aggregation quality, and difficulty in inferring topic proportions for individual documents. |
| Approach: | They propose a model which constructs global clustering contexts for short texts using text embeddings from pre-trained language models. |
| Outcome: | The proposed model outperforms state-of-the-art models on short texts in topic quality and document representation. |
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