Dinh Phung

LiveCultureBench: a Multi-Agent, Multi-Cultural Benchmark for Large Language Models in Dynamic Social Simulations ACL 2026 Boosting Multiple Views for pretrained-based Continual Learning ICLR 2025 Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective ICCV 2025 Planning for Success: Exploring LLM Long-term Planning Capabilities in Table Understanding CONLL 2025 Improving Generalization with Flat Hilbert Bayesian Inference ICML 2025 Neural Topic Modeling with Large Language Models in the Loop ACL 2025 Planning for Success: Exploring LLM Long-term Planning Capabilities in Table Understanding ACL 2025 Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation CVPR 2025 Enhancing Dataset Distillation via Non-Critical Region Refinement CVPR 2025 PanSplat: 4K Panorama Synthesis with Feed-Forward Gaussian Splatting CVPR 2025 Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models ICML 2025 PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction ICLR 2025 Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them ICLR 2025 Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation NIPS 2024 Text-Enhanced Data-free Approach for Federated Class-Incremental Learning CVPR 2024 Taming Stable Diffusion for Text to 360 Panorama Image Generation CVPR 2024 Optimal Transport for Structure Learning Under Missing Data ICML 2024 Parameter Estimation in DAGs from Incomplete Data via Optimal Transport ICML 2024 Frequency Attention for Knowledge Distillation WACV 2024 Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization NIPS 2024 NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation CVPR 2024 Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation ICLR 2024 MetaAug: Meta-Data Augmentation for Post-Training Quantization ECCV 2024 Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs ACL 2024 An Additive Instance-Wise Approach to Multi-class Model Interpretation ICLR 2023 Optimal Transport Model Distributional Robustness NIPS 2023 Flat Seeking Bayesian Neural Networks NIPS 2023 Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning NIPS 2023 Global-Local Regularization Via Distributional Robustness AISTATS 2023 Systematic Assessment of Factual Knowledge in Large Language Models EMNLP 2023 Vector Quantized Wasserstein Auto-Encoder ICML 2023 Adversarial Local Distribution Regularization for Knowledge Distillation WACV 2023 On Transportation of Mini-batches: A Hierarchical Approach ICML 2022 Bridging Global Context Interactions for High-Fidelity Image Completion CVPR 2022 On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds AISTATS 2022 Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out Training ACL 2022 Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics AISTATS 2022 Stochastic Multiple Target Sampling Gradient Descent NIPS 2022 Can Domains Be Transferred across Languages in Multi-Domain Multilingual Neural Machine Translation? EMNLP 2022 A Unified Wasserstein Distributional Robustness Framework for Adversarial Training ICLR 2022 Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation UAI 2022 Particle-based Adversarial Local Distribution Regularization AISTATS 2022 A Vietnamese-English Neural Machine Translation System INTERSPEECH 2022 MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation NIPS 2022 On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources NIPS 2021 LAMDA: Label Matching Deep Domain Adaptation ICML 2021 Quaternion Graph Neural Networks ACML 2021 Most: multi-source domain adaptation via optimal transport for student-teacher learning UAI 2021 On efficient multilevel Clustering via Wasserstein distances JMLR 2021 Topic Modelling Meets Deep Neural Networks: A Survey IJCAI 2021 Optimal Transport for Deep Generative Models: State of the Art and Research Challenges IJCAI 2021 TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport IJCAI 2021 Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection EMNLP 2021 STEM: An Approach to Multi-Source Domain Adaptation With Guarantees ICCV 2021 Neural Topic Model via Optimal Transport ICLR 2021 Exploiting Domain-Specific Features to Enhance Domain Generalization NIPS 2021 Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness AAAI 2021 Variational Autoencoders for Sparse and Overdispersed Discrete Data AISTATS 2020 Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering COLING 2020 Effective Unsupervised Domain Adaptation with Adversarially Trained Language Models EMNLP 2020 Parameterized Rate-Distortion Stochastic Encoder ICML 2020 OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling NIPS 2020 A Relational Memory-based Embedding Model for Triple Classification and Search Personalization ACL 2020 Improving Adversarial Robustness by Enforcing Local and Global Compactness ECCV 2020 Learning Generative Adversarial Networks from Multiple Data Sources IJCAI 2019 Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection ICLR 2019 Learning How to Active Learn by Dreaming ACL 2019 Robust Anomaly Detection in Videos Using Multilevel Representations AAAI 2019 Three-Player Wasserstein GAN via Amortised Duality IJCAI 2019 A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization NAACL 2019 Probabilistic Multilevel Clustering via Composite Transportation Distance AISTATS 2019 Batch Normalized Deep Boltzmann Machines ACML 2018 Geometric Enclosing Networks IJCAI 2018 Clustering Induced Kernel Learning ACML 2018 MGAN: Training Generative Adversarial Nets with Multiple Generators ICLR 2018 A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network NAACL 2018 Discriminative Bayesian Nonparametric Clustering IJCAI 2017 Dual Discriminator Generative Adversarial Nets NIPS 2017 Approximation Vector Machines for Large-scale Online Learning JMLR 2017 Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017 Multilevel Clustering via Wasserstein Means ICML 2017 Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data MLHC 2016 Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016 Multiple Kernel Learning with Data Augmentation ACML 2016 Dual Space Gradient Descent for Online Learning NIPS 2016 Streaming Variational Inference for Dirichlet Process Mixtures ACML 2015 Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts ICML 2014 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013 Thurstonian Boltzmann Machines: Learning from Multiple Inequalities ICML 2013 Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine ACML 2013 Learning From Ordered Sets and Applications in Collaborative Ranking ACML 2012 Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis ACML 2012 Mixed-Variate Restricted Boltzmann Machines ACML 2011 Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data NIPS 2008