Jiangchao Yao
51 papers · 2018–2026 · 9 venues · across top CS/AI venues
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Research topics
Machine Learning
(43)
Deep Learning
(26)
Learning Types Β· Machine Learning
(24)
Artificial Intelligence
(18)
Application Areas
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Core Methods
(17)
Core AI
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Computer Vision
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Models
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Optimization & Theory
(9)
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(3)
Keywords
graph neural network
(6)
representation learning
(5)
federated learning
(5)
self-supervised learning
(5)
large language model
(4)
long-tailed distribution
(4)
multimodal learning
(4)
label noise
(3)
link prediction
(3)
knowledge distillation
(3)
out-of-distribution detection
(3)
class imbalance
(3)
generative model
(3)
domain generalization
(3)
contrastive learning
(3)
diffusion model
(3)
image generation
(2)
distribution shift
(2)
collaborative learning
(2)
deep learning
(2)
Papers
GenMask: Adapting DiT for Segmentation via Direct Mask Generation
CVPR 2026
One-Step Diffusion Transformer for Controllable Real-World Image Super-Resolution
CVPR 2026
Rejection Mixing: Fast Semantic Propagation of Mask Tokens for Efficient DLLM Inference
CVPR 2026
CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
ICML 2025
Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning
ICCV 2025
Fast and Accurate Blind Flexible Docking
ICLR 2025
From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?
ICML 2025
LamRA: Large Multimodal Model as Your Advanced Retrieval Assistant
CVPR 2025
Large Language Models Enhanced Personalized Graph Neural Architecture Search in Federated Learning
AAAI 2025
MetaNeRV: Meta Neural Representations for Videos with Spatial-Temporal Guidance
AAAI 2025
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
ICML 2025
Multi-modal Medical Diagnosis via Large-small Model Collaboration
CVPR 2025
Towards Regularized Mixture of Predictions for Class-Imbalanced Semi-Supervised Facial Expression Recognition
IJCAI 2025
Diversified Batch Selection for Training Acceleration
ICML 2024
Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
ICLR 2024
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
ICML 2024
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs
ICLR 2024
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization
ICML 2024
Long-tailed Diffusion Models with Oriented Calibration
ICLR 2024
Low-Rank Knowledge Decomposition for Medical Foundation Models
CVPR 2024
Mitigating Label Noise on Graphs via Topological Sample Selection
ICML 2024
Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning
CVPR 2024
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
ICLR 2024
On Harmonizing Implicit Subpopulations
ICLR 2024
Probabilistic Conformal Distillation for Enhancing Missing Modality Robustness
NeurIPS 2024
ReMamber: Referring Image Segmentation with Mamba Twister
ECCV 2024
Reprogramming Distillation for Medical Foundation Models
MICCAI 2024
Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
NeurIPS 2024
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
NeurIPS 2024
Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning
ICML 2024
Class-Balancing Diffusion Models
CVPR 2023
Combating Bilateral Edge Noise for Robust Link Prediction
NeurIPS 2023
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
ICLR 2023
Combating Representation Learning Disparity with Geometric Harmonization
NeurIPS 2023
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation
NeurIPS 2023
Exploring Model Dynamics for Accumulative Poisoning Discovery
ICML 2023
Federated Domain Generalization With Generalization Adjustment
CVPR 2023
Federated Learning with Bilateral Curation for Partially Class-Disjoint Data
NeurIPS 2023
Long-Tailed Partial Label Learning via Dynamic Rebalancing
ICLR 2023
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
AAAI 2023
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
ICML 2023
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
NeurIPS 2023
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
ICML 2023
Contrastive Learning with Boosted Memorization
ICML 2022
Reliable Adversarial Distillation with Unreliable Teachers
ICLR 2022
Learning with Group Noise
AAAI 2021
How does Disagreement Help Generalization against Label Corruption?
ICML 2019
Safeguarded Dynamic Label Regression for Noisy Supervision
AAAI 2019
Understanding VAEs in Fisher-Shannon Plane
AAAI 2019
Collaborative Learning for Weakly Supervised Object Detection
IJCAI 2018
Masking: A New Perspective of Noisy Supervision
NeurIPS 2018