Papers by Tien-Phat Nguyen
LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models (2026.acl-long)
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| Challenge: | Existing cross-lingual topic models depend on sparse bilingual resources and often yield incoherent or weakly aligned topics. |
| Approach: | They propose a framework that integrates LLM-guided topic refinement with self-consistency uncertainty quantification to enable black-box, stable, and scalable enhancement of cross-lingual topic models. |
| Outcome: | Experiments on multilingual corpora show that the proposed framework achieves superior topic coherence and alignment while reducing reliance on bilingual dictionaries and expensive LLM calls. |
Z-GMOT: Zero-shot Generic Multiple Object Tracking (2024.findings-naacl)
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Kim Tran, Anh Duy Le Dinh, Tien-Phat Nguyen, Thinh Phan, Pha Nguyen, Khoa Luu, Donald Adjeroh, Gianfranco Doretto, Ngan Le
| Challenge: | Existing approaches to Multi-Object Tracking (MOT) rely on initial bounding boxes and struggle with unseen objects. |
| Approach: | They propose a cutting-edge multi-object tracking solution that can track unseen objects . they propose iGLIP and MA-SORT, which integrate motion and appearance matching strategies . |
| Outcome: | The proposed solution can track objects from never-seen categories without initial bounding boxes or predefined categories. |