Nguyen, Dang

20 publications

NeurIPS 2025 ColorBench: Can VLMs See and Understand the Colorful World? a Comprehensive Benchmark for Color Perception, Reasoning, and Robustness Yijun Liang, Ming Li, Chenrui Fan, Ziyue Li, Dang Nguyen, Kwesi Adu Cobbina, Shweta Bhardwaj, Jiuhai Chen, Fuxiao Liu, Tianyi Zhou

ICLR 2025 Mini-Batch Coresets for Memory-Efficient Language Model Training on Data Mixtures Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman

ICML 2025 Synthetic Text Generation for Training Large Language Models via Gradient Matching Dang Nguyen, Zeman Li, Mohammadhossein Bateni, Vahab Mirrokni, Meisam Razaviyayn, Baharan Mirzasoleiman

AAAI 2024 COMBAT: Alternated Training for Effective Clean-Label Backdoor Attacks Tran Huynh, Dang Nguyen, Tung Pham, Anh Tran

ECML-PKDD 2024 Improving Diversity in Black-Box Few-Shot Knowledge Distillation Tri-Nhan Vo, Dang Nguyen, Kien Do, Sunil Gupta

ACML 2024 Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior Giang Ngo, Dang Nguyen, Sunil Gupta

ICLR 2024 Understanding the Robustness of Multi-Modal Contrastive Learning to Distribution Shift Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman

ACML 2023 Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta

ICML 2023 Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction Khai Nguyen, Dang Nguyen, Nhat Ho

ECCV 2022 Black-Box Few-Shot Knowledge Distillation Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh

ICML 2022 Improving Mini-Batch Optimal Transport via Partial Transportation Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho

NeurIPS 2022 Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation Kien Do, Thai Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh

ICML 2022 On Transportation of Mini-Batches: A Hierarchical Approach Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho

ECCV 2022 Towards Effective and Robust Neural Trojan Defenses via Input Filtering Kien Do, Haripriya Harikumar, Hung Le, Dung Nguyen, Truyen Tran, Santu Rana, Dang Nguyen, Willy Susilo, Svetha Venkatesh

ECML-PKDD 2021 Fast Conditional Network Compression Using Bayesian HyperNetworks Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh

ECML-PKDD 2021 Knowledge Distillation with Distribution Mismatch Dang Nguyen, Sunil Gupta, Trong Nguyen, Santu Rana, Phuoc Nguyen, Truyen Tran, Ky Le, Shannon Ryan, Svetha Venkatesh

AAAI 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh

ECML-PKDD 2020 Bayesian Optimization with Missing Inputs Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh

ICML 2020 DeepCoDA: Personalized Interpretability for Compositional Health Data Thomas Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh

ECML-PKDD 2018 Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung