I am a researcher working at the intersection of NLP, computer vision, and multimodal learning, with a focus on large multimodal models and video understanding. I received my PhD from the National University of Singapore in September 2025, advised by Professor See-Kiong Ng and Professor Anh-Tuan Luu. My research focuses on building and understanding multimodal models for language, vision, and video.

Specifically, my research program centers on grounding multimodal models in time — building systems that base their predictions on concrete visual evidence in dynamic environments, rather than producing fluent but ungrounded answers. It is organized along three directions:

  1. Building and benchmarking temporal grounding systems. Architectures and benchmarks that force models to recover the temporal evidence supporting their predictions, not just produce plausible final answers. [DemaFormer (EMNLP’23)] [Motion-aware Contrastive (AAAI’25)] [Multi-Scale Contrastive (AAAI’25)]

  2. Learning from partial temporal supervision. Treating noisy, incomplete video–text alignment as a core modeling challenge so that models avoid spurious correlations and adapt efficiently under realistic data. [MAMA (ECCV’24)] [READ (AAAI’24)]

  3. Visual foresight. Anticipating future visual states via retrieval-grounded prediction and physics-aware motion-guided animation, rather than free-form generative hallucination. [Eulerian Motion Guidance (ACM MM’26)]

My broader vision is to build the temporal infrastructure that makes autonomous multimodal agents trustworthy in dynamic environments — turning temporal grounding from a niche task into a core architectural requirement for reliable multimodal intelligence.

I am grateful to the Institute of Data Science (IDS), NUS, for sharing my research and my journey toward building trustworthy multimodal AI through temporal grounding and visual evidence.

I am open to opportunities for collaboration and new research ideas. If you are interested in working with me, please feel free to contact via my email.

Outside research, I take photos when I travel. A few of them are here.

News

Oct 27, 2026 🏆 Our paper Don’t Read Everything receives the Best Paper Award at EMNLP 2026.
Sep 23, 2026 🎤 I visit the Multimodal AI Lab at TU Darmstadt, hosted by Professor Anna Rohrbach and Professor Marcus Rohrbach, and give a talk: From Seeing to Justifying: Towards Reliable Multimodal Understanding.
Aug 29, 2026 🏆 Our paper Don’t Read Everything is nominated for an award at EMNLP 2026.
Aug 21, 2026 🎉 Two papers accepted to EMNLP 2026 (Main Conference).
Jul 10, 2026 🎉 One paper accepted to ACM Multimedia 2026.
Jun 22, 2026 🎤 I give a talk at the RAIVN Lab, University of Washington: Grounding Multimodal Models in Time: From Temporal Evidence to Visual Foresight.
Jun 11, 2026 🧑‍⚖️ I am invited to serve as Area Chair for EMNLP 2026.
Mar 24, 2026 🧑‍⚖️ I am invited to serve as Area Chair for NeurIPS 2026.
Feb 4, 2026 🏆 I receive the Student Research Award from the Institute of Data Science, National University of Singapore.
Sep 2, 2025 🎓 I successfully defend my PhD thesis: Video Understanding - Through a Temporal Lens.
Apr 9, 2025 🧑‍⚖️ I am invited to serve as Area Chair for NeurIPS 2025.
Jan 17, 2025 🏆 I receive the Student Research Award from the Institute of Data Science, National University of Singapore.
Dec 10, 2024 🎉 Two papers accepted to AAAI 2025.
Oct 25, 2024 🧑‍⚖️ I am invited to serve as Area Chair for NAACL 2025.
Sep 26, 2024 🎉 One paper accepted to NeurIPS 2024.
Sep 20, 2024 🎉 One paper accepted to EMNLP 2024.
Jul 2, 2024 🎉 One paper accepted to ECCV 2024.
Jun 21, 2024 🧑‍⚖️ I am invited to serve as Area Chair for EMNLP 2024.
May 16, 2024 🎉 Two papers accepted to ACL 2024.
Mar 14, 2024 🎉 One paper accepted to NAACL 2024.
Dec 20, 2023 🎉 One paper accepted to Artificial Intelligence Review.
Dec 10, 2023 🎉 Two papers accepted to AAAI 2024.

Selected Publications

For the full list of my publications: Publications, Google Scholar.

  1. ACM MM’26
    Eulerian Motion Guidance: Robust Image Animation via Bidirectional Geometric Consistency
    Thong Nguyen, Khoi M. Le, Cong-Duy Nguyen, Anh Tuan Luu, See-Kiong Ng, Chunyan Miao
    In Proceedings of the 34th ACM International Conference on Multimedia
  2. EMNLP’26
    Don’t Read Everything: A Curvature-Conditioned Query for Linear Attention
    Dong Le, Thong Nguyen, Cong-Duy Nguyen, Luu Anh Tuan
    In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
    Best Paper Award
  3. EMNLP’26
    When In-Distribution Gains Fail: Evaluating Weak-to-Strong Reward Models under Preference Shift
    Khoi Le, Tri Cao, Phong Nguyen, Cong-Duy Nguyen, Luu Anh Tuan, Chunyan Miao, See-Kiong Ng, Thong Nguyen
    In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
  4. SAC’26
    More Bias, Less Bias: BiasPrompting for Enhanced Multiple-Choice Question Answering
    Duc Anh Vu, Thong Nguyen, Cong-Duy Nguyen, Viet Anh Nguyen, Luu Anh Tuan
    In Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing
  5. AAAI’25
    Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation
    Thong Nguyen, Xiaobao Wu, Yi Bin, Cong-Duy Nguyen, See-Kiong Ng, Anh Tuan Luu
    In Proceedings of the 39th AAAI Conference on Artificial Intelligence
  6. AAAI’25
    Multi-Scale Contrastive Learning for Video Temporal Grounding
    Thong Nguyen, Yi Bin, Xiaobao Wu, Zhiyuan Hu, Cong-Duy Nguyen, See-Kiong Ng, Anh Tuan Luu
    In Proceedings of the 39th AAAI Conference on Artificial Intelligence
  7. NAACL’25
    Enhancing Multimodal Entity Linking with Jaccard Distance-based Conditional Contrastive Learning and Contextual Visual Augmentation
    Cong-Duy Nguyen, Xiaobao Wu, Thong Nguyen, Shuai Zhao, Khoi M. Le, Viet Anh Nguyen, Yichao Feng, Luu Anh Tuan
    In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics
  8. SAC’25
    Curriculum Demonstration Selection for In-Context Learning
    Duc Anh Vu, Cong-Duy Nguyen, Xiaobao Wu, Nhat Hoang, Mingzhe Du, Thong Nguyen, Luu Anh Tuan
    In Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing
  9. NeurIPS’24
    FASTopic: A Fast, Adaptive, Stable, and Transferable Topic Modeling Paradigm
    Xiaobao Wu, Thong Nguyen, Delvin Ce Zhang, William Yang Wang, Anh Tuan Luu
    In Advances in Neural Information Processing Systems
  10. EMNLP’24
    Encoding and Controlling Global Semantics for Long-form Video Question Answering
    Thong Nguyen, Zhiyuan Hu, Xiaobao Wu, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan
    In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  11. ECCV’24
    MAMA: A Meta-optimized Angular Margin Contrastive Framework for Video-Language Representation Learning
    Thong Nguyen, Yi Bin, Xiaobao Wu, Xinshuai Dong, Zhiyuan Hu, Khoi Le, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan
    In Proceedings of the 18th European Conference on Computer Vision
  12. ACL’24
    Video-Language Understanding: A Survey from Model Architecture, Model Training, and Data Perspectives
    Thong Nguyen, Yi Bin, Junbin Xiao, Leigang Qu, Yicong Li, Jay Zhangjie Wu, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan
    In Proceedings of Findings of 62nd Annual Meeting of the Association for Computational Linguistics
  13. NAACL’24
    KDMCSE: Knowledge distillation multimodal sentence embeddings with adaptive angular margin contrastive learning
    Cong-Duy Nguyen, Thong Nguyen, Xiaobao Wu, Luu Anh Tuan
    In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics
  14. AAAI’24
    On the affinity, rationality, and diversity of hierarchical topic modeling
    Xiaobao Wu, Fengjun Pan, Thong Nguyen, Yichao Feng, Chaoqun Liu, Cong-Duy Nguyen, Luu Anh Tuan
    In Proceedings of the 38th AAAI Conference on Artificial Intelligence
  15. ICLR’24
    Topic Modeling as Multi-Objective Contrastive Optimization
    Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan
    In Proceedings of International Conference on Learning Representations
  16. ACL’24
    Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusion
    Xiaobao Wu, Xinshuai Dong, Liangming Pan, Thong Nguyen, Luu Anh Tuan
    In Proceedings of Findings of 62nd Annual Meeting of the Association for Computational Linguistics
  17. AAAI’24
    READ: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling
    Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Khoi Le, Zhiyuan Hu, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan
    In Proceedings of the 38th AAAI Conference on Artificial Intelligence
  18. ACM MM’23
    Expand BERT Representation with Visual Information via Grounded Language Learning with Multimodal Partial Alignment
    Cong-Duy Nguyen, The-Anh Vu-Le, Thong Nguyen, Tho Quan, Luu Anh Tuan
    In Proceedings of the 31st ACM International Conference on Multimedia
  19. EMNLP’23
    Improving multimodal sentiment analysis: Supervised angular margin-based contrastive learning for enhanced fusion representation
    Cong-Duy Nguyen, Thong Nguyen, Duc Vu, Luu Anh Tuan
    In Proceedings of Findings of 2023 Conference on Empirical Methods in Natural Language Processing
  20. ICML’23
    Effective Neural Topic Modeling with Embedding Clustering Regularization
    Xiaobao Wu, Xinshuai Dong, Thong Nguyen, Luu Anh Tuan
    In Proceedings of the 40th International Conference on Machine Learning
  21. EMNLP’23
    DemaFormer: Damped Exponential Moving Average Transformer with Energy-Based Modeling for Temporal Language Grounding
    Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan
    In Proceedings of Findings of 2023 Conference on Empirical Methods in Natural Language Processing
  22. AAAI’23
    InfoCTM: A Mutual Information Maximization Perspective of Cross-lingual Topic Modeling
    Xiaobao Wu, Xinshuai Dong, Thong Nguyen, Chaoqun Liu, Liangming Pan, Luu Anh Tuan
    In Proceedings of the 37th AAAI Conference on Artificial Intelligence
  23. ACL’23
    Gradient-Boosted Decision Tree for Listwise Context Model in Multimodal Review Helpfulness Prediction
    Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Luu Anh Tuan, Cong-Duy Nguyen, Zhen Hai, Lidong Bing
    In Proceedings of Findings of 61st Annual Meeting of the Association for Computational Linguistics
  24. EMNLP’22
    Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions
    Thong Nguyen, Xiaobao Wu, Luu Anh Tuan, Cong-Duy Nguyen, Zhen Hai, Lidong Bing
    In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  25. AAAI’22
    Improving Neural Cross-Lingual Abstractive Summarization via Employing Optimal Transport Distance for Knowledge Distillation
    Thong Nguyen, Luu Anh Tuan
    In Proceedings of the 36th AAAI Conference on Artificial Intelligence
  26. NeurIPS’21
    Contrastive Learning for Neural Topic Model
    Thong Nguyen, Luu Anh Tuan
    In Advances in Neural Information Processing Systems
  27. EMNLP’21
    Enriching and Controlling Global Semantics for Text Summarization
    Thong Nguyen, Luu Anh Tuan, Truc Lu, Tho Quan
    In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing