Nguyen, Dung

24 publications

NeurIPS 2025 Controlling the Spread of Epidemics on Networks with Differential Privacy Dung Nguyen, Aravind Srinivasan, Renata Valieva, Anil Vullikanti, Jiayi Wu
IJCAI 2025 Localizing Before Answering: A Benchmark for Grounded Medical Visual Question Answering Dung Nguyen, Minh Khoi Ho, Huy D. Ta, Thanh Tam Nguyen, Qi Chen, Kumar Rav, Quy Duong Dang, Satwik Ramchandre, Son Lam Phung, Zhibin Liao, Minh-Son To, Johan Verjans, Phi Le Nguyen, Vu Minh Hieu Phan
AAAI 2025 Multi-Reference Preference Optimization for Large Language Models Hung Le, Quan Hung Tran, Dung Nguyen, Kien Do, Saloni Mittal, Kelechi Ogueji, Svetha Venkatesh
IJCAI 2025 Navigating Social Dilemmas with LLM-Based Agents via Consideration of Future Consequences Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran
TMLR 2025 Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models Hung Le, Van Dai Do, Dung Nguyen, Svetha Venkatesh
ICLR 2025 Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning Hung Le, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
AISTATS 2024 Computing Epidemic Metrics with Edge Differential Privacy George Z. Li, Dung Nguyen, Anil Vullikanti
WACV 2024 Contrastive Viewpoint-Aware Shape Learning for Long-Term Person Re-Identification Vuong D. Nguyen, Khadija Khaldi, Dung Nguyen, Pranav Mantini, Shishir Shah
ICML 2024 Differentially Private Exact Recovery for Stochastic Block Models Dung Nguyen, Anil Kumar Vullikanti
IJCAI 2024 Diversifying Training Pool Predictability for Zero-Shot Coordination: A Theory of Mind Approach Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran
TMLR 2024 Plug, Play, and Generalize: Length Extrapolation with Pointer-Augmented Neural Memory Hung Le, Dung Nguyen, Kien Do, Svetha Venkatesh, Truyen Tran
IJCAI 2023 Differentially Private Partial Set Cover with Applications to Facility Location George Z. Li, Dung Nguyen, Anil Vullikanti
WACV 2023 EmbryosFormer: Deformable Transformer and Collaborative Encoding-Decoding for Embryos Stage Development Classification Tien-Phat Nguyen, Trong-Thang Pham, Tri Nguyen, Hieu Le, Dung Nguyen, Hau Lam, Phong Nguyen, Jennifer Fowler, Minh-Triet Tran, Ngan Le
NeurIPS 2023 Faster Approximate Subgraph Counts with Privacy Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan, Anil Vullikanti
AAAI 2023 Memory-Augmented Theory of Mind Network Dung Nguyen, Phuoc Nguyen, Hung Le, Kien Do, Svetha Venkatesh, Truyen Tran
WACV 2023 PP4AV: A Benchmarking Dataset for Privacy-Preserving Autonomous Driving Linh Trinh, Phuong Pham, Hoang Trinh, Nguyen Bach, Dung Nguyen, Giang Nguyen, Huy Nguyen
IJCAI 2023 Social Motivation for Modelling Other Agents Under Partial Observability in Decentralised Training Dung Nguyen, Hung Le, Kien Do, Svetha Venkatesh, Truyen Tran
ICML 2022 Differentially Private Community Detection for Stochastic Block Models Mohamed S Mohamed, Dung Nguyen, Anil Vullikanti, Ravi Tandon
AAAI 2022 Episodic Policy Gradient Training Hung Le, Majid Abdolshah, Thommen George Karimpanal, Kien Do, Dung Nguyen, Svetha Venkatesh
NeurIPS 2022 Learning to Constrain Policy Optimization with Virtual Trust Region Thai Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh
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
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
ICML 2021 Differentially Private Densest Subgraph Detection Dung Nguyen, Anil Vullikanti
ACML 2020 Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen, Truyen Tran