Papers by Quang Duc Nguyen
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. |
Sharpness-Aware Minimization for Topic Models with High-Quality Document Representations (2025.naacl-long)
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Tung Nguyen, Tue Le, Hoang Tran Vuong, Quang Duc Nguyen, Duc Anh Nguyen, Linh Ngo Van, Sang Dinh, Thien Huu Nguyen
| Challenge: | Recent advances in topic models have significantly enhanced the performance compared to conventional probabilistic approaches. |
| Approach: | They propose to use a topic model optimization method to improve generalization and performance. |
| Outcome: | The proposed method improves topic models on popular benchmark datasets. |