Jiangchao Yao

48 papers · 2018–2025 · 9 conferences · across top CS/AI conferences

Achievements

+15 more ↓

🌍 Conference Polyglot (9) 🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird

🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🤝 Dynamic Duo (26) 👑 Triple Crown 🏆 Grand Slam 🌱 Topic Pioneer 🏆 Keyword Champion 📈 Trend Setter 🚀 Conference Pioneer 🗃️ Keyword Collector (144) ⚡ Prolific Year (17) ❓ The Questioner (2) 💎 Century Club (48) 🔥 Unstoppable (5)

Conferences

ICML (13) ICLR (9) NIPS (9) AAAI (6) CVPR (6) IJCAI (2) ECCV (1) ICCV (1) MICCAI (1)

Top co-authors

Ya Zhang (26) Bo Han (24) Yanfeng Wang (20) Tongliang Liu (8) Jianing Zhu (6) Feng Hong (6) Gang Niu (5) Zhanke Zhou (5) Zihua Zhao (5) Quanming Yao (4)

Keywords

representation learning (5) self-supervised learning (4) out-of-distribution detection (3) long-tailed distribution (3) multimodal learning (3) federated learning (3) contrastive learning (3) graph neural network (3) vision-language model (2) distribution shift (2) generative model (2) collaborative learning (2) domain generalization (2) noisy label (2) deep learning (2) noisy label learning (2) class imbalance (2) weakly supervised learning (2) knowledge distillation (2) link prediction (2)

Papers

Multi-modal Medical Diagnosis via Large-small Model Collaboration CVPR 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 CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration ICML 2025 Fast and Accurate Blind Flexible Docking ICLR 2025 Towards Regularized Mixture of Predictions for Class-Imbalanced Semi-Supervised Facial Expression Recognition IJCAI 2025 From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? ICML 2025 MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition ICML 2025 Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning ICCV 2025 Reprogramming Distillation for Medical Foundation Models MICCAI 2024 Probabilistic Conformal Distillation for Enhancing Missing Modality Robustness NIPS 2024 Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection NIPS 2024 Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation NIPS 2024 Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning CVPR 2024 Low-Rank Knowledge Decomposition for Medical Foundation Models CVPR 2024 ReMamber: Referring Image Segmentation with Mamba Twister ECCV 2024 On Harmonizing Implicit Subpopulations ICLR 2024 Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel ICLR 2024 Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs ICLR 2024 Long-tailed Diffusion Models with Oriented Calibration ICLR 2024 Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts ICLR 2024 Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization ICML 2024 Diversified Batch Selection for Training Acceleration ICML 2024 Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning ICML 2024 Mitigating Label Noise on Graphs via Topological Sample Selection ICML 2024 Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters ICML 2024 Combating Bilateral Edge Noise for Robust Link Prediction NIPS 2023 Combating Representation Learning Disparity with Geometric Harmonization NIPS 2023 NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension AAAI 2023 Federated Domain Generalization With Generalization Adjustment CVPR 2023 Class-Balancing Diffusion Models CVPR 2023 Exploring Model Dynamics for Accumulative Poisoning Discovery ICML 2023 Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability ICML 2023 Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation NIPS 2023 Long-Tailed Partial Label Learning via Dynamic Rebalancing ICLR 2023 Combating Exacerbated Heterogeneity for Robust Models in Federated Learning ICLR 2023 Federated Learning with Bilateral Curation for Partially Class-Disjoint Data NIPS 2023 Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation NIPS 2023 On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation ICML 2023 Contrastive Learning with Boosted Memorization ICML 2022 Reliable Adversarial Distillation with Unreliable Teachers ICLR 2022 Learning with Group Noise AAAI 2021 Safeguarded Dynamic Label Regression for Noisy Supervision AAAI 2019 Understanding VAEs in Fisher-Shannon Plane AAAI 2019 How does Disagreement Help Generalization against Label Corruption? ICML 2019 Collaborative Learning for Weakly Supervised Object Detection IJCAI 2018 Masking: A New Perspective of Noisy Supervision NIPS 2018