← Authors

Trung Le

76 papers · 2016–2026 · 17 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (9) 🌍 Conference Polyglot (16) 🐝 Cross-Pollinator (8) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (21) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (53) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (12) πŸ”₯ Unstoppable (10) πŸš€ Conference Pioneer ⚑ Prolific Year (9) πŸ—ƒοΈ Keyword Collector (248) πŸ“ˆ Trend Setter πŸ’Ž Century Club (70)

Conferences

NIPS (13) ICML (10) ICLR (10) IJCAI (6) AAAI (5) CVPR (5) EMNLP (5) AISTATS (4) ICCV (3) EACL (3) ACML (3) ECCV (2) UAI (2) WACV (2) COLING (1) JMLR (1) NAACL (1)

Top co-authors

Dinh Phung (53) He Zhao (12) Tu Dinh Nguyen (10) Thanh-Toan Do (9) Quyen Tran (9) Quan Hung Tran (8) nhαΊ­t Hα»“ (8) Linh Ngo Van (8) Mehrtash Harandi (7) Hung Bui (7)

Research topics

Privacy (1)

Keywords

knowledge distillation (11) optimal transport (11) domain adaptation (8) model compression (7) wasserstein distance (6) generative model (4) generative adversarial network (4) unsupervised domain adaptation (4) neural network (4) adversarial example (4) adversarial robustness (3) bayesian neural network (3) label shift (3) stochastic gradient descent (3) multi-source domain adaptation (3) domain generalization (3) variational inference (3) image generation (3) transfer learning (3) multi-objective optimization (3)

Papers

Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models EACL 2026
Causal Direct Preference Optimization for Language Model Alignment EACL 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
DWA-KD: Dual-Space Weighting and Time-Warped Alignment for Cross-Tokenizer Knowledge Distillation EACL 2026
A Good Teacher Adapts Their Knowledge for Distillation ICCV 2025
Mutual-pairing Data Augmentation for Fewshot Continual Relation Extraction NAACL 2025
Improving Generalization with Flat Hilbert Bayesian Inference ICML 2025
RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts ICML 2025
Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective ICCV 2025
XTRA: Cross-Lingual Topic Modeling with Topic and Representation Alignments EMNLP 2025
Multi-Surrogate-Objective Optimization for Neural Topic Models EMNLP 2025
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models ICML 2025
Improved Training Technique for Latent Consistency Models 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
NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics ICLR 2025
Boosting Multiple Views for pretrained-based Continual Learning ICLR 2025
Erasing Undesirable Influence in Diffusion Models CVPR 2025
Enhancing Dataset Distillation via Non-Critical Region Refinement CVPR 2025
Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation CVPR 2025
EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments EMNLP 2025
MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora EMNLP 2025
MetaAug: Meta-Data Augmentation for Post-Training Quantization ECCV 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
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
Frequency Attention for Knowledge Distillation WACV 2024
Vector Quantized Wasserstein Auto-Encoder ICML 2023
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning NIPS 2023
An Additive Instance-Wise Approach to Multi-class Model Interpretation ICLR 2023
Optimal Transport Model Distributional Robustness NIPS 2023
Adversarial Local Distribution Regularization for Knowledge Distillation WACV 2023
Flat Seeking Bayesian Neural Networks NIPS 2023
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics NIPS 2023
Global-Local Regularization Via Distributional Robustness AISTATS 2023
AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity NIPS 2023
Stochastic Multiple Target Sampling Gradient Descent NIPS 2022
STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers NIPS 2022
On Transportation of Mini-batches: A Hierarchical Approach ICML 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
STEM: An Approach to Multi-Source Domain Adaptation With Guarantees ICCV 2021
Neural Topic Model via Optimal Transport ICLR 2021
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness AAAI 2021
LAMDA: Label Matching Deep Domain Adaptation ICML 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
Most: multi-source domain adaptation via optimal transport for student-teacher learning UAI 2021
Parameterized Rate-Distortion Stochastic Encoder ICML 2020
Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering COLING 2020
Improving Adversarial Robustness by Enforcing Local and Global Compactness ECCV 2020
Robust Anomaly Detection in Videos Using Multilevel Representations AAAI 2019
Three-Player Wasserstein GAN via Amortised Duality IJCAI 2019
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection ICLR 2019
Learning Generative Adversarial Networks from Multiple Data Sources IJCAI 2019
Clustering Induced Kernel Learning ACML 2018
Geometric Enclosing Networks IJCAI 2018
MGAN: Training Generative Adversarial Nets with Multiple Generators ICLR 2018
Batch Normalized Deep Boltzmann Machines ACML 2018
Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017
Approximation Vector Machines for Large-scale Online Learning JMLR 2017
Discriminative Bayesian Nonparametric Clustering IJCAI 2017
Dual Discriminator Generative Adversarial Nets NIPS 2017
Dual Space Gradient Descent for Online Learning NIPS 2016
Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016
Multiple Kernel Learning with Data Augmentation ACML 2016