Multilinguality and Language Technology

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1. Ho Minh Duy Nguyen; Hasan Md Tusfiqur Alam; Tai Nguyen; Devansh Srivastav; Hans-Jürgen Profitlich; Ngan Le; Daniel Sonntag

   Deep Learning for Ophthalmology - The State-of-the-Art and Future Trends

   DFKI, DFKI Research Reports (RR), Vol. 01, 2024.

2. Ho Minh Duy Nguyen; Nina Lukashina; Tai Nguyen; An T. Le; TrungTin Nguyen; Nhat Ho; Jan Peters; Daniel Sonntag; Viktor Zaverkin; Mathias Niepert

   Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks

   In: Proceedings of the 41st International Conference on Machine Learning. International Conference on Machine Learning (ICML), July 21-27, Austria, JMLR.org, 2024.

3. Hoai-Chau Tran; Ho Minh Duy Nguyen; Manh-Duy Nguyen; Ngan Hoang Le; Binh T. Nguyen

   Energy Minimizing-based Token Merging for Accelerating Transformers

   In: International Conference on Learning Representations (ICLR), Practical ML for Low Resource Settings Workshop. International Conference on Learning Representations (ICLR), May 11-12, JMLR.org, 2024.

4. Hoai-Chau Tran; Ho Minh Duy Nguyen; Duy M. Nguyen; TrungTin Nguyen; Ngan Le; Pengtao Xie; Daniel Sonntag; James Zou; Binh T. Nguyen; Mathias Niepert

   Accelerating Transformers with Spectrum-Preserving Token Merging

   In: The Thirty-Eighth Annual Conference on Neural Information Processing Systems. Neural Information Processing Systems (NeurIPS-2024), December 10-15, Canada, JMLR.org, 2024.

5. Ho Minh Duy Nguyen; An T. Le; Trung Q. Nguyen; Nghiem T. Diep; Tai Nguyen; Duy Duong-Tran; Jan Peters; Li Shen; Mathias Niepert; Daniel Sonntag

   Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model

   In: The 16th Asian Conference on Machine Learning. Asian Conference on Machine Learning (ACML-2024), December 5-8, Proceedings of Machine Learning Research, 2024.

6. Ho Minh Duy Nguyen; Hoang Nguyen; Nghiem T. Diep; Tan Pham; Tri Cao; Binh T. Nguyen; Paul Swoboda; Nhat Ho; Shadi Albarqouni; Pengtao Xie; Daniel Sonntag; Mathias Niepert

   LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

   In: The Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS 2023). Neural Information Processing Systems (NeurIPS), December 10-16, USA, Advances in Neural Information Processing Systems, 12/2023.

7. Ho Minh Duy Nguyen; Tan Pham; Nghiem Tuong Diep; Nghi Phan; Quang Pham; Vinh Tong; Binh T. Nguyen; Ngan Hoang Le; Nhat Ho; Pengtao Xie; Daniel Sonntag; Mathias Niepert

   On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

   In: The Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS 2023). Neural Information Processing Systems (NeurIPS), Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models, December 10-16, Advances in Neural Information Processing Systems, 12/2023.

8. Ho Minh Duy Nguyen; Hoang Nguyen; Mai T. N. Truong; Tri Cao; Binh T. Nguyen; Nhat Ho; Paul Swoboda; Shadi Albarqouni; Pengtao Xie; Daniel Sonntag

   Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering

   In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2023). AAAI Conference on Artificial Intelligence (AAAI), February 7-14, Washington, DC, USA, AAAI Press, 2/2023.

9. Michael Barz; Omair Shahzad Bhatti; Hasan Md Tusfiqur Alam; Ho Minh Duy Nguyen; Daniel Sonntag

   Interactive Fixation-to-AOI Mapping for Mobile Eye Tracking Data Based on Few-Shot Image Classification

   In: Companion Proceedings of the 28th International Conference on Intelligent User Interfaces. International Conference on Intelligent User Interfaces (IUI-2023), Sydney, NSW, Australia, Pages 175-178, IUI '23 Companion, ISBN 9798400701078, Association for Computing Machinery, 2023.

10. Ho Minh Duy Nguyen; Thu T. Nguyen; Huong Vu; Quang Pham; Manh-Duy Nguyen; Binh T. Nguyen; Daniel Sonntag

    TATL: Task Agnostic Transfer Learning for Skin Attributes Detection

    In: Medical Image Analysis, Vol. 01, Pages 1-27, Elsevier, 2022.

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