Thanh-Toan Do
31 papers · 2015–2026 · 12 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (11) π Academic Marathon (10) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (11)
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Cross-Pollinator
(11)
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Renaissance Researcher
(6)
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Taxonomy Completionist
(52)
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Topic Evolution
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Dynamic Duo
(12)
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Grand Slam
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Unstoppable
(9)
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Keyword Collector
(119)
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Century Club
(29)
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Prolific Year
(5)
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Conference Pioneer
Conferences
CVPR (6)
WACV (5)
ECCV (4)
NIPS (3)
AAAI (2)
ICCV (2)
ICLR (2)
ICML (2)
IJCAI (2)
ACL (1)
EMNLP (1)
UAI (1)
Top co-authors
Keywords
knowledge distillation
(4)
model compression
(3)
bayesian neural network
(3)
variational inference
(2)
frequency domain
(2)
few-shot learning
(2)
generative model
(2)
multi-modal learning
(2)
deep learning
(2)
posterior inference
(2)
optimal transport
(2)
student model
(2)
data augmentation
(2)
image retrieval
(2)
instance segmentation
(2)
latent dirichlet allocation
(1)
image segmentation
(1)
embedding space
(1)
bayesian inference
(1)
image classification
(1)
Papers
Coverage-Constrained Human-AI Cooperation with Multiple Experts
AAAI 2026
Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models
ACL 2026
Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution
ICLR 2025
MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora
EMNLP 2025
CamoFA: A Learnable Fourier-Based Augmentation for Camouflage Segmentation
WACV 2025
Enhancing Dataset Distillation via Non-Critical Region Refinement
CVPR 2025
Multi-Perspective Data Augmentation for Few-shot Object Detection
ICLR 2025
Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation
CVPR 2025
Learning to Complement and to Defer to Multiple Users
ECCV 2024
MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation
AAAI 2024
Frequency Attention for Knowledge Distillation
WACV 2024
Sharpness-Aware Data Generation for Zero-shot Quantization
ICML 2024
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation
ECCV 2024
MetaAug: Meta-Data Augmentation for Post-Training Quantization
ECCV 2024
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
Instance-Dependent Noisy Label Learning via Graphical Modelling
WACV 2023
Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-Width Deep Neural Networks
WACV 2023
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification (Extended Abstract)
IJCAI 2022
Probabilistic task modelling for meta-learning
UAI 2021
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
WACV 2020
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
IJCAI 2020
Bayesian Generative Active Deep Learning
ICML 2019
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences
CVPR 2019
Scalable Place Recognition Under Appearance Change for Autonomous Driving
ICCV 2019
Compact Trilinear Interaction for Visual Question Answering
ICCV 2019
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
CVPR 2019
Bayesian Semantic Instance Segmentation in Open Set World
ECCV 2018
Simultaneous Feature Aggregating and Hashing for Large-Scale Image Search
CVPR 2017
FAemb: A Function Approximation-Based Embedding Method for Image Retrieval
CVPR 2015