Trung Le

DWA-KD: Dual-Space Weighting and Time-Warped Alignment for Cross-Tokenizer Knowledge Distillation EACL 2026 Causal Direct Preference Optimization for Language Model Alignment EACL 2026 TALAS: Teacher-Anchored Layer Alignment with Adaptive Sharpness-Aware Minimization for Embedding Distillation ACL 2026 MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation ACL 2026 LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models ACL 2026 CTPD: Cross Tokenizer Preference Distillation AAAI 2026 MCW-KD: Multi-Cost Wasserstein Knowledge Distillation for Large Language Models AAAI 2026 DIET: Machine Unlearning on a Data-Diet AAAI 2026 Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models ACL 2026 SRA: Span Representation Alignment for Large Language Model Distillation ACL 2026 Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models EACL 2026 Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models ICML 2025 Improved Training Technique for Latent Consistency Models ICLR 2025 Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation CVPR 2025 Boosting Multiple Views for pretrained-based Continual Learning ICLR 2025 NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics ICLR 2025 Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts ICLR 2025 Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them ICLR 2025 Erasing Undesirable Influence in Diffusion Models CVPR 2025 RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts ICML 2025 MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora EMNLP 2025 EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments EMNLP 2025 Multi-Surrogate-Objective Optimization for Neural Topic Models EMNLP 2025 XTRA: Cross-Lingual Topic Modeling with Topic and Representation Alignments EMNLP 2025 Enhancing Dataset Distillation via Non-Critical Region Refinement CVPR 2025 Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective ICCV 2025 A Good Teacher Adapts Their Knowledge for Distillation ICCV 2025 Improving Generalization with Flat Hilbert Bayesian Inference ICML 2025 Mutual-pairing Data Augmentation for Fewshot Continual Relation Extraction NAACL 2025 Preserving Generalization of Language models in Few-shot Continual Relation Extraction EMNLP 2024 Sharpness-Aware Data Generation for Zero-shot Quantization ICML 2024 Parameter Estimation in DAGs from Incomplete Data via Optimal Transport ICML 2024 Optimal Transport for Structure Learning Under Missing Data ICML 2024 Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization NIPS 2024 Enhancing Domain Adaptation through Prompt Gradient Alignment NIPS 2024 Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation NIPS 2024 Text-Enhanced Data-free Approach for Federated Class-Incremental Learning CVPR 2024 NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation CVPR 2024 MetaAug: Meta-Data Augmentation for Post-Training Quantization ECCV 2024 Frequency Attention for Knowledge Distillation WACV 2024 Adversarial Local Distribution Regularization for Knowledge Distillation WACV 2023 AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity NIPS 2023 An Additive Instance-Wise Approach to Multi-class Model Interpretation ICLR 2023 Global-Local Regularization Via Distributional Robustness AISTATS 2023 Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning NIPS 2023 Learning Time-Invariant Representations for Individual Neurons from Population Dynamics NIPS 2023 Flat Seeking Bayesian Neural Networks NIPS 2023 Optimal Transport Model Distributional Robustness NIPS 2023 Vector Quantized Wasserstein Auto-Encoder ICML 2023 On Transportation of Mini-batches: A Hierarchical Approach ICML 2022 STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers NIPS 2022 Stochastic Multiple Target Sampling Gradient Descent NIPS 2022 Particle-based Adversarial Local Distribution Regularization AISTATS 2022 On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds AISTATS 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 Most: multi-source domain adaptation via optimal transport for student-teacher learning UAI 2021 STEM: An Approach to Multi-Source Domain Adaptation With Guarantees ICCV 2021 LAMDA: Label Matching Deep Domain Adaptation ICML 2021 Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness AAAI 2021 On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources NIPS 2021 TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport IJCAI 2021 Neural Topic Model via Optimal Transport ICLR 2021 Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering COLING 2020 Parameterized Rate-Distortion Stochastic Encoder ICML 2020 Improving Adversarial Robustness by Enforcing Local and Global Compactness ECCV 2020 Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection ICLR 2019 Three-Player Wasserstein GAN via Amortised Duality IJCAI 2019 Learning Generative Adversarial Networks from Multiple Data Sources IJCAI 2019 Robust Anomaly Detection in Videos Using Multilevel Representations AAAI 2019 MGAN: Training Generative Adversarial Nets with Multiple Generators ICLR 2018 Geometric Enclosing Networks IJCAI 2018 Batch Normalized Deep Boltzmann Machines ACML 2018 Clustering Induced Kernel Learning ACML 2018 Discriminative Bayesian Nonparametric Clustering IJCAI 2017 Dual Discriminator Generative Adversarial Nets NIPS 2017 Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017 Approximation Vector Machines for Large-scale Online Learning JMLR 2017 Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016 Multiple Kernel Learning with Data Augmentation ACML 2016 Dual Space Gradient Descent for Online Learning NIPS 2016