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)] [STEMO (arXiv’26)]

  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.

My research is featured by the Institute of Data Science (IDS), NUS.

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.

News

Jul 10, 2026 🎉 One paper accepted to ACM Multimedia 2026.
Jun 22, 2026 🎤 Gave an invited talk at the RAIVN Lab, University of Washington: Grounding Multimodal Models in Time: From Temporal Evidence to Visual Foresight.
Jun 11, 2026 🧑‍⚖️ Invited to serve as Area Chair for EMNLP 2026
Mar 24, 2026 🧑‍⚖️ Invited to serve as Area Chair for NeurIPS 2026
Sep 2, 2025 🎓 Succesfully defended my PhD thesis: Video Understanding - Through a Temporal Lens
Apr 9, 2025 🧑‍⚖️ Invited to serve as Area Chair for NeurIPS 2025.
Dec 10, 2024 🎉 Two papers accepted to AAAI 2025.
Oct 25, 2024 🧑‍⚖️ 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 🧑‍⚖️ 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. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. NeurIPS’21
    Contrastive Learning for Neural Topic Model
    Thong Nguyen, Luu Anh Tuan
    In Advances in Neural Information Processing Systems
  13. 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