Tianyang Hu
25 papers · 2021–2025 · 12 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge Β· Bronze π Conference Polyglot Β· Gold πΊοΈ Taxonomy Completionist (40) π Triple Crown
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Keyword Champion
(2)
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Keyword Pioneer
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Triple Crown
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Keyword Collector
(119)
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Century Club Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(19)
Deep Learning
(16)
Models
(9)
Optimization & Theory Β· Machine Learning
(9)
Core Methods
(8)
Computer Vision
(7)
Generation
(7)
Learning Types Β· Machine Learning
(6)
Artificial Intelligence
(5)
Learning Types Β· Deep Learning
(5)
Optimization & Theory Β· Deep Learning
(5)
Application Areas
(4)
Architectures
(4)
Core AI
(4)
Mathematics & Optimization
(1)
Keywords
contrastive learning
(4)
representation learning
(4)
diffusion model
(3)
self-supervised learning
(3)
image generation
(3)
diffusion distillation
(2)
text-to-image synthesis
(2)
diffusion probabilistic model
(2)
pre-trained model
(2)
decision boundary
(2)
vision-language model
(2)
neural tangent kernel
(2)
knowledge distillation
(2)
domain generalization
(2)
out-of-distribution generalization
(2)
curse of dimensionality
(2)
deep neural network
(2)
generative model
(2)
classifier-free guidance
(2)
one-step generation
(2)
Papers
Adding Additional Control to One-Step Diffusion with Joint Distribution Matching
ICCV 2025
Elucidating the design space of language models for image generation
ICML 2025
Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data
NAACL 2025
Learning Few-Step Diffusion Models by Trajectory Distribution Matching
ICCV 2025
Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary
JMLR 2025
Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism
EMNLP 2025
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs
ICLR 2025
Accelerating Diffusion Sampling with Optimized Time Steps
CVPR 2024
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning
IJCAI 2024
Elucidating the design space of classifier-guided diffusion generation
ICLR 2024
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers
ICML 2024
JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation
ECCV 2024
Random Smoothing Regularization in Kernel Gradient Descent Learning
JMLR 2024
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
ICML 2024
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling
ICML 2024
Complexity Matters: Rethinking the Latent Space for Generative Modeling
NeurIPS 2023
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-Real Novel View Synthesis via Contrastive Learning
CVPR 2023
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
NeurIPS 2023
Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification
UAI 2023
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization
ICML 2023
Inducing Neural Collapse in Deep Long-tailed Learning
AISTATS 2023
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding
ICLR 2023
Understanding Square Loss in Training Overparametrized Neural Network Classifiers
NeurIPS 2022
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
NeurIPS 2022
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
AISTATS 2021