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    2026
  • L. Meng, T. Yang, Y. Zhang, Z. Ge, Y. Gao. “Faster Game Solving via Asymmetry of Step Sizes.” AAAI Conference on Artificial Intelligence (AAAI), 2026.
  • H. Cao, T. Yang, F. Feng, H. R. Ouariachi, Y. Du, M. Fang, J. Huo, Y. Gao. “Causality-aware Efficient Exploration for Cooperative Multi-agent Reinforcement Learning.” AAAI Conference on Artificial Intelligence (AAAI), 2026.
  • Z. Chen, C. Gao, L. Shao, J. Shi, J. Huo, Y. Gao. “ManiLong-Shot: Interaction-aware One-shot Imitation Learning for Long-horizon Manipulation.” AAAI Conference on Artificial Intelligence (AAAI), 2026.
  • Z. Liu, B. Kang, W. Li, H. Yuan, Y. Yang, W. Li, J. Luo, Y. Zhu, T. Feng. “Branch, or Layer? Zeroth-Order Optimization for Continual Learning of Vision-Language Models.” The 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026.
  • S. Gan, J. Liu, B. Wang, T. Yang, R. Miao, Y. Zhang, F. Meng, J. Feng, L. Meng, et al. “Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning.” Annual Meeting of the Association for Computational Linguistics (ACL), 2026.
  • Z. Chen, X. Feng, J. Shi, L. Shao, J. Huo, Y. Gao. “AGiLe: Learning Robust Long-Horizon Manipulation via Affordance-Grounded Bidirectional Latent Planning.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • S. Li, J. Guo, J. Zhang, Y. Zhou, L. Cao, Y. Shi. “Duala: Dual-Level Alignment of Subjects and Stimuli for Cross-Subject fMRI Decoding.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • Z. Fa, Y. Duan, J. Zhang, L. Qi, Y. Shi. “One Token, Two Fates: A Unified Framework via Vision Token Manipulation Against MLLMs Hallucination.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • S. Liu, Y. Yin, L. Wang, Q. Fan, Y. Shi, W. Li, Y. Gao, D. Tao. “Understanding and Enforcing Weight Disentanglement in Task Arithmetic.” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • Z. Duan, Z. Zhang, F. Lu, S. Zhang, W. Li, Q. Fan, Y. Gao. “SAME: Sparse and Anchored Model Editing for Heterogeneous Incremental Learning under Limited Data.” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • J. Ma, X. Xiang, W. Li, Q. Fan, Y. Gao. “Selective, Regularized, and Calibrated: Harnessing Vision Foundation Models for Cross-Domain Few-Shot Semantic Segmentation.” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • Q. Tang, C. Liu, S. Zhang, W. Li, Q. Fan, Y. Gao. “Prompt-Free Universal Region Proposal Network.” The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  • X. Xiang, Z. Duan, G. Zhang, H. Zhang, Z. Gao, J. Wu, S. Zhang, T. Wang, Q. Fan, C. Guo. “Pathwise Test-Time Correction for Autoregressive Long Video Generation.” European Conference on Computer Vision (ECCV), 2026.
  • S. Guo, S. He, C. Meng, S. Xiao, X. Xiang, S. Zhang, Q. Fan. “PhyEditBench: A Real-World Multi-Stage Benchmark for Physics-Aware Image Editing.” European Conference on Computer Vision (ECCV), 2026.
  • H. Fan, X. Han, X. Bao, Z. Gao, Q. Fan, Y. Song, J. Jiang. “BIP: Bi-level Information Transfer and Completion Prompting for Visual Recognition with Missing Modalities.” European Conference on Computer Vision (ECCV), 2026.
  • J. Yang, A. Chen, Y. Dang, Q. Fan, C. Wang, W. Li, M. Feng, Y. Gao. “HART: High-Resolution Annotation-Free Reasoning Technique through a Closed-loop Framework.” European Conference on Computer Vision (ECCV), 2026.
  • F. Lu, J. Feng, Z. Zhou, S. Zhang, W. Li, Q. Fan, Y. Gao. “SEERBench: A Spatial Ego-Exo Reasoning Benchmark for MLLMs with a Simple Yet Effective Baseline.” European Conference on Computer Vision (ECCV), 2026.
  • Z. Gao, T. Chai, S. Shen, W. Wang, H. Xu, W. Xing, W. Li, Q. Fan, Y. Gao, D. Tao. “VideoTIR: Accurate and Efficient Understanding for Long Videos with Tool-Integrated Reinforcement Learning.” European Conference on Computer Vision (ECCV), 2026.
  • H. Cao, S. Jing, Y. Wang, Z. Peng, Z. Bai, Z. Cao, M. Fang, F. Feng, J. Liu, et al. “SafeDialBench: A Fine-grained Safety Evaluation Benchmark for Large Language Models in Multi-turn Dialogues with Diverse Jailbreak Attacks.” International Conference on Learning Representations (ICLR), 2026.
  • Z. Duan, F. Lu, X. Xiang, W. Li, Y. Gao, Q. Fan. “Retain and Adapt: Auto-Balanced Model Editing for Open-Vocabulary Object Detection under Domain Shifts.” The International Conference on Learning Representations (ICLR), 2026.
  • F. Lu, Z. Duan, X. Xiang, Z. Zhang, W. Li, Y. Gao, Q. Fan. “QPrompt-R1: Real-Time Reasoning for Domain-Generalized Semantic Segmentation via Group-Relative Query Alignment.” The International Conference on Learning Representations (ICLR), 2026.
  • L. Meng, Y. Zhang, S. Yang, W. Li, T. Ding, Y. Gao. “Faster Parameter-Free Regret Matching Algorithms.” The International Conference on Learning Representations (ICLR), 2026.
  • T. Wu, J. Zhang, Y. Gao. “Furina: Fragmented Uncertainty-Driven Refusal Instability Attack.” International Conference on Machine Learning (ICML), 2026.
  • Q. Ma, Z. Zhao, Y. Wu, J. Zhang, L. Bai, Y. Shi. “Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning.” International Conference on Machine Learning (ICML), 2026.
  • Y. Li, Z. Peng, J. Zhang, J. Guo, Y. Duan, Y. Shi. “When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging.” International Conference on Machine Learning (ICML), 2026.
  • B. Kang, J. Gu, T. Feng, Q. Fan, Y. Shi, L. Wang, W. Li, Y. Gao. “Don't Forget Why You Started: Tackling Dual Forgetting in Vision-Language Continual Learning.” International Conference on Machine Learning (ICML), 2026.
  • L. Wen, X. Zhu, L. Huang, W. Li, Y. Gao. “The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models.” International Conference on Machine Learning (ICML), 2026.
  • Y. Dang, M. Dai, Y. Yang, N. Zhang, W. Li, M. Feng, Y. Gao. “UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing.” International Conference on Machine Learning (ICML), 2026.
  • Z. Wei, Y. Dong, Z. Li, X. Lin, X. Liu, H. Gu, S. Zhang, W. Li, Q. Fan. “SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models.” International Conference on Machine Learning (ICML), 2026.
  • Z. Li, Y. Shi, Y. Gao, D. Xu. “Diffusion-Based Data Augmentation for Image Recognition: A Systematic Analysis and Evaluation.” International Journal of Computer Vision (IJCV), 2026.
  • J. Chen, Q. Fan, Z. Quan, D. Li, X. Zheng, H. Murase, D. Deguchi. “Training-Free Open-Vocabulary Semantic Segmentation with Context Pyramid Refinement.” International Journal of Computer Vision (IJCV), 2026.
  • C. Xu, S. Li, J. Zhang, Y. Shi. “BRAIN: Bi-directional Motion Reasoning with Dynamic Memory Pruning for Surgical Video Segmentation.” Medical Image Computing and Computer Assisted Intervention (MICCAI), 2026.
  • W. Zhang, S. Li, J. Zhang, L. Qi, L. Lin, Q. Yu, Y. Fang, Y. Shi. “HK-Fuse: Hilbert-Interleaved Kimi Delta Attention for Incomplete-Modality Brain Tumor Segmentation.” Medical Image Computing and Computer Assisted Intervention (MICCAI), 2026.
  • L. Cao, Z. Wu, J. Zhang, L. Qi, Y. Gao, H. Zheng, Y. Zheng, Y. Shi. “An All in One Foundation Model for Multimodal Medical Image Restoration and Enhancement.” Nature Machine Intelligence (NMI), 2026.
  • Z. Wei, X. Guo, X. Li, X. Xiang, M. Wei, Y. Zhu, Q. Wang, X. Wang, P. Wan, X. Hou, Q. Fan. “Geometry-Aware Implicit Memory for Video World Models.” SIGGRAPH Asia, 2026.
  • Z. Duan, X. Xiang, Y. Chen, H. Huang, C. Zhang, Q. Fan, X. Li. “Uncertainty DMD: Restoring Diversity in Few-Step Autoregressive Video Distillation.” SIGGRAPH Asia, 2026.
  • J. Zhang, L. Qi, Y. Shi, Y. Gao. “MVDG++: A Unified Multi-view Framework for Domain Generalization.” IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2026.
  • X. Wang, J. Zhang, L. Qi, Y. Gao, Y. Shi. “Exploring Dualistic Meta-Learning to Enhance Domain Generalization in Open Set Scenarios.” IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2026.
  • Z. Peng, J. Zhang, L. Qi, Y. Gao, Y. Shi. “Towards the Connection between Activation Sparsity and Flat Minima.” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.
  • Y. Bao, T. Ding, J. Huo, W. Li, Y. Gao. “FISN: Finding Spatial Neighborhoods for Generalizable Novel View Synthesis.” IEEE Transactions on Visualization and Computer Graphics (TVCG), 2026.
  • Y. Duan, Y. Shi, Z. Yuan, Z. Zhang, L. Qi, C. Wang, Y. Shi. “Unified Multimodal Model Proficient in Continued Training.” ACM Conference on Multimedia (ACM MM), 2026.
  • L. Cao, J. Zhang, Z. Li, L. Qi, Y. Shi. “Training Medical Volumetric Super-Resolution Model in ONLY One Epoch.” ACM Conference on Multimedia (ACM MM), 2026.
    • 2025
  • Y. Li, J. Guo, L. Qi, W. Li, Y. Shi. “Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP.” AAAI Conference on Artificial Intelligence (AAAI), 2025.
  • Y. Chen, T. Ding, L. Wang, J. Huo, Y. Gao, W. Li. “Enhancing Few-shot Class-incremental Learning via Training-free Bi-level Modality Calibration.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  • Q. Ma, J. Zhang, Z. Li, L. Qi, Q. Yu, Y. Shi. “Steady Progress Beats Stagnation: Mutual Aid of Foundation and Conventional Models in Mixed Domain Semi-Supervised Medical Image Segmentation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  • X. Wang, J. Zhang, L. Qi, Y. Shi. “Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  • M. Yang, Z. Li, J. Zhang, L. Qi, Y. Shi. “Taste More, Taste Better: Diverse Data and Strong Model Boost Semi-Supervised Crowd Counting.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
  • Q. Fan, K.-Q. Liu, N. Liu, H. Cholakkal, R. M. Anwer, W. Li, Y. Gao. “Adapting In-Domain Few-Shot Segmentation to New Domains without Retraining” IEEE/CVF International Conference on Computer Vision (ICCV), 2025.
  • Z. Peng, J. Zhang, Y. Wang, L. Qi, Y. Shi, Y. Gao. “Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD.” International Conference on Learning Representations (ICLR), 2025.
  • Y. Chen, Z. Chen, J. Yin, J. Huo, P. Tian, J. Shi, Y. Gao. “GravMAD: Grounded Spatial Value Maps Guided Action Diffusion for Generalized 3D Manipulation.” International Conference on Learning Representations (ICLR), 2025.
  • Q. Fan, X. Tao, K. Lei, M. Ye, Y. Zhang, P. Wan, Y.-W. Tai, C.-K. Tang. “Stable Segment Anything Model” International Conference on Learning Representations (ICLR), 2025.
  • H. Cao, F. Feng, M. Fang, S. Dong, T. Yang, J. Huo, Y. Gao. “Towards Empowerment Gain through Causal Structure Learning in Model-Based RL” International Conference on Learning Representations (ICLR), 2025.
  • H. Cao, F. Feng, T. Yang, J. Huo, Y. Gao. “Causal Information Prioritization for Efficient Reinforcement Learning” International Conference on Learning Representations (ICLR), 2025.
  • L. Meng, Y. Zhang, W. Chen, W. Li, T. Yang, Y. Gao. “Reducing Variance of Stochastic Optimization for Approximating Nash Equilibria in Normal-Form Games” International Conference on Machine Learning (ICML), 2025.
  • S. Schoepp, M. Jafaripour, Y. Cao, T. Yang, F. Abdollahi, S. Golestan, Z. Sufiyan, O. R. Zaiane, M. E. Taylor. “The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning” Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2025 Survey Track.
  • J. Chen, D. Deguchi, D. Li, X. Zheng, S. Ito, H. Murase, Q. Fan. “Semantic-Centric Alignment for Zero-shot Panoptic Segmentation with Limited Data.” International Journal of Computer Vision (IJCV), 2025.
  • Q. Fan, M. Segu, B. Schiele, D. Dai, Y.-W. Tai, C.-K. Tang. “Robust Object Detection with Domain-Invariant Training and Continual Test-Time Adaptation” International Journal of Computer Vision (IJCV), 2025.
  • S. Li, J. Zhang, L. Qi, Y. Shi. “GA-SAM: Geometry-Aware SAM Adaptation with Sparse Annotation-Driven Point Cloud Completion.” Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
  • G. Yang, T. Yang, J. Qiao, Y. Wu, J. Huo, X. Chen, Y. Gao. “Multi-Agent Reinforcement Learning with Communication-Constrained Priors.” Advances in Neural Information Processing Systems (NeurIPS), 2025.
  • L. Meng, Y. Zhang, Z. Ge, T. Ding, S. Yang, Z. Xu, W. Li, Y. Gao. “Last-Iterate Convergence of Smooth Regret Matching+ Variants in Learning Nash Equilibria.” The Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
  • L. Meng, Y. Zhang, S. Yang, T. Ding, Z. Ge, W. Li, T. Yang, B. An, Y. Gao. “Efficient Last-Iterate Convergence in Solving Extensive-Form Games.” The Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
  • C.-H. Liu, X. Xiang, Z. Duan, W. Li, Y. Gao, Q. Fan. “Don’t Need Retraining: A Mixture of DETR and Vision Foundation Models for Cross-Domain Few-Shot Object Detection.” The Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
  • H. Cao, F. Feng, J. Huo, Y. Gao. “Causal Action Empowerment for Efficient Reinforcement Learning in Embodied Agents.” Science China Information Sciences, 2025.
  • Y. Duan, L. Qi, Y. Shi, Y. Gao. “An Adaptor for Triggering Semi-supervised Learning to Out-of-Box Serve Deep Image Clustering.” IEEE Transactions on Image Processing (TIP), 2025.
  • D. Ren, W. Li, T. Ding, J. Huo, L. Wang, H. Pan, Y. Gao. “Leveraging Frequency Analysis for Image Denoising Network Pruning” IEEE Transactions on Image Processing (TIP), 2025.
  • X. Zhou, H. Yu, S. Yang, J. Huo, P. Tian. “Learning from Orthogonal Space with Multimodal Large Models for Generalized Few-shot Segmentation.” ACM Transactions on Multimedia Computing, Communications and Applications (TOMM), 2025.
  • J. Huo, S. Jin, J. Li, P. Tian, W. Li, J. Wu, Y.-K. Lai, Y. Gao. “Dictionary-based Generative Adversarial Network for Multi-collection Style Transfer.” IEEE Transactions on Multimedia (TMM), 2025.
  • D. Ren, W. Li, T. Ding, L. Wang, Q. Fan, J. Huo, H. Pan, Y. Gao. “ONNXPruner: ONNX-Based General Model Pruning Adapter” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
  • L. Cao, H. Xu, J. Zhang, L. Qi, J. Ma, Y. Shi, Y. Gao. “Towards Perfection: Building Inter-component Mutual Correction for Retinex-based Low-light Image Enhancement.” ACM Conference on Multimedia (ACM MM), 2025.
    • 2024
  • F. Wang, W. Huang, S. Yang, Q. Fan, L. Lan. “Learning to Learn Better Visual Prompts.” AAAI Conference on Artificial Intelligence (AAAI), 2024.
  • Y. Duan, Z. Zhao, L. Qi, L. Zhou, L. Wang, Y. Shi. “Roll With the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-grained Learning.” AAAI Conference on Artificial Intelligence (AAAI), 2024.
  • T. Chen, Y. Duan, D. Li, L. Qi, Y. Shi, Y. Gao. “PG-LBO: Enhancing High-dimensional Bayesian Optimization with Pseudo-label and Gaussian Process Guidance.” AAAI Conference on Artificial Intelligence (AAAI), 2024.
  • C. Li, Y. Zhang, J. Wang, Y. Hu, S. Dong, W. Li, T. Lv, C. Fan, Y. Gao. “Optimistic Value Instructors for Cooperative Multi-Agent Reinforcement Learning.” AAAI Conference on Artificial Intelligence (AAAI), 2024.
  • J. Su, Q. Fan, W. Pei, G. Lu, F. Chen. “Domain-Rectifying Adapter for Cross-domain Few-Shot Segmentation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  • Q. Ma, J. Zhang, L. Qi, Q. Yu, Y. Shi, Y. Gao. “Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  • W. Deng, W. Li, T. Ding, L. Wang, H. Zhang, K. Huang, J. Huo, Y. Gao. “Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  • M. Qiu, J. Zhang, L. Qi, Q. Yu, Y. Shi, Y. Gao. “The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation.” European Conference on Computer Vision (ECCV), 2024.
  • Y. Bao, T. Ding, J. Huo, W. Li, Y. Li, Y. Gao. “InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules.” International Conference on Learning Representations (ICLR), 2024.
  • C. Li, Y. Hu, S. Yang, T. Lv, C. Fan, W. Li, C. Zhang, Y. Gao. “STAR: Spatio-Temporal State Compression for Multi-Agent Tasks with Rich Observations.” Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI), 2024.
  • Q. Fan, Z. Wei, C.-K. Tang, Y.-W. Tai. “FSODv2: A Deep Calibrated Few-Shot Object Detection Network.” International Journal of Computer Vision (IJCV), 2024.
  • J. Guo, L. Qi, Y. Shi, Y. Gao. “START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation.” Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.
  • L. Qi, H. Yang, Y. Shi, X. Geng. “NormAUG: Normalization-guided Augmentation for Domain Generalization.” IEEE Transactions on Image Processing (TIP), 2024.
  • N. Wang, L. Qi, J. Guo, Y. Shi, Y. Gao. “Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations.” IEEE Transactions on Image Processing (TIP), 2024.
  • J. Zhang, L. Qi, Y. Shi, Y. Gao. “Exploring Flat Minima for Domain Generalization with Large Learning Rates.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
  • Z. Li, L. Qi, Y. Li, Y. Shi, Y. Gao. “Open-Domain Semi-Supervised Learning via Glocal Cluster Structure Exploitation.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
  • L. Qi, H. Yang, Y. Shi, X. Geng. “MultiMatch: Multi-task Learning for Semi-supervised Domain Generalization.” ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2024.
  • Y. Duan, Z. Gu, Z. Ying, L. Qi, C. Meng, Y. Shi. “PC2: Pseudo-Classification Based Pseudo-Captioning for Noisy Correspondence Learning in Cross-Modal Retrieval.” ACM Conference on Multimedia (ACM MM), 2024.
    • 2023
  • W. Chen, W. Li, X. Liu, S. Yang, Y. Gao. Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy Gradient. In: AAAI Conference on Artificial Intelligence (AAAI'23), 2023.
  • L. Meng, Z. Ge, P. Tian, B. An, Y. G. D. F.-O. A. E. D. R. L. A. F. S. I. I. E.-F. Games. ". In: AAAI Conference on Artificial Intelligence (AAAI'23), 2023.
  • J. Guo, N. Wang, L. Qi, Y. Shi. “ALOFT: A Lightweight MLP-like Architecture with Dynamic Low-Frequency Transform for Domain Generalization.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  • L. Yang, L. Qi, L. Feng, W. Zhang, Y. Shi. “Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  • H. Cai, S. Li, L. Qi, Q. Yu, Y. Shi, Y. Gao. “Orthogonal Annotation Benefits Barely-supervised Medical Image Segmentation.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  • W. Li, Z. Fan, J. Huo, Y. Gao. Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR'23), 2023.
  • J. Zhang, L. Qi, Y. Shi, Y. Gao. “DomainAdaptor: A Novel Approach to Test-time Adaptation.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • Z. Li, L. Qi, Y. Shi, Y. Gao. “IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • J. Guo, L. Qi, Y. Shi. “DomainDrop: Suppressing Domain-Sensitive Channels for Domain Generalization.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • L. Yang, Z. Zhao, L. Qi, Q. Yu, Y. Shi, H. Zhao. “Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • Y. Duan, Z. Zhao, L. Qi, L. Zhou, L. Wang, Y. Shi. “Class Transition Tracking Based Pseudo-Rectifying Guidance for Semi-supervised Learning with Non-random Missing Labels.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • G. Guan, Z. Zhao, L. Qi, L. Zhou, L. Wang, Y. Shi. “Enhancing Sample Utilization through Sample Adaptive Augmentation in Semi-Supervised Learning.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • X. Wang, J. Zhang, L. Qi, Y. Shi. “Generalizable Decision Boundaries: Dualistic Meta-Learning for Open Set Domain Generalization.” IEEE/CVF International Conference on Computer Vision (ICCV), 2023.
  • M. Zhang, J. Yuan, Y. He, W. Li, Z. Chen, K. Kuang. “MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters.” International Conference on Computer Vision (ICCV), 2023.
  • Q. Fan, M. Segu, Y.-W. Tai, F. Yu, C.-K. Tang, B. Schiele, D. Dai. “Towards Robust Object Detection Invariant to Real-World Domain Shifts.” International Conference on Learning Representations (ICLR), 2023.
  • H. Cai, L. Qi, Q. Yu, Y. Shi, Y. Gao. “3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D Networks.” Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023.
  • L. Yang, X. Xu, B. Kang, Y. Shi, H. Zhao. “FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models.” Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS), 2023.
  • J. Guo, L. Qi, Y. Shi, Y. Gao. “PLACE dropout: A Progressive Layer-wise and Channel-wise Dropout for Domain Generalization.” ACM Transactions on Multimedia Computing Communications and Applications (TOMM), 2023.
  • P. Zheng, H. Fu, D.-P. Fan, Q. Fan, J. Qin, Y.-W. Tai, C.-K. Tang, L. V. Gool. “GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  • W. Li, Z. Wang, X. Yang, C. Dong, P. Tian, T. Qin, J. Huo, Y. Shi, L. Wang, Y. Gao, J. Luo. “LibFewShot: A Comprehensive Library for Few-shot Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  • W. Li, L. Wang, X. Zhang, L. Qi, J. Huo, Y. Gao, J. Luo. “Defensive Few-shot Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  • Y. Bao, Y. Li, J. Huo, T. Ding, X. Liang, W. Li, Y. Gao. “Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs.” ACM Conference on Multimedia (ACM MM), 2023.
    • 2022
  • Z. Zhao, L. Zhou, L. Wang, Y. Shi, Y. Gao. “LaSSL: Label-guided Self-training for Semi-supervised Learning.” AAAI Conference on Artificial Intelligence (AAAI), 2022.
  • L. Yang, Z. Wei, L. Qi, Y. Shi, Y. Gao. “ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  • Z. Zhou, L. Qi, X. Yang, N. Dong, Y. Shi. “Generalizable Cross-modality Medical Image Segmentation via Style Augmentation and Dual Normalization.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  • Z. Zhao, L. Zhou, Y. Duan, L. Wang, L. Qi, Y. Shi. “DC-SSL: Addressing Mismatched Class Distribution in Semi-supervised Learning.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  • M. Zhang, S. Huang, W. Li, D. Wang. Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation. In: European Conference on Computer Vision (ECCV'22), 2022.
  • J. Zhang, L. Qi, Y. Shi, Y. Gao. “MVDG: A Unified Multi-view Framework for Domain Generalization.” European Conference on Computer Vision (ECCV), 2022.
  • Z. Zhou, L. Qi, Y. Shi. “Generalizable Medical Image Segmentation via Random Amplitude Mixup and Domain-Specific Image Restoration.” European Conference on Computer Vision (ECCV), 2022.
  • Y. Duan, L. Qi, L. Wang, L. Zhou, Y. Shi. “RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning.” European Conference on Computer Vision (ECCV), 2022.
  • M. Zhang, S. Huang, W. Li, D. Wang. “Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation.” European Conference on Computer Vision (ECCV), 2022.
  • G. Guan, Z. Zhao, L. Qi, L. Zhou, L. Wang, Y. Shi. “Improving Barely Supervised Learning by Discriminating Unlabeled Samples with Super-Class.” Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.
  • J. Huo, X. Liu, W. Li, Y. Gao, H. Yin, J. Luo. CAST: Learning Both Geometric and Texture Style Transfers for Effective Caricature Generation. In: IEEE Transactions on Image Processing (TIP), 2022.
  • Q. Yu, L. Qi, Y. Gao, W. Wang, Y. Shi. “Crosslink-Net: Double-Branch Encoder Network via Fusing Vertical and Horizontal Convolutions for Medical Image Segmentation.” IEEE Transactions on Image Processing (TIP), 2022.
  • L. Qi, L. Wang, Y. Shi, X. Geng. “A Novel Mix-normalization Method for Generalizable Multi-source Person Re-identification.” IEEE Transactions on Multimedia (TMM), 2022.
  • W. Li, L. Wang, X. Zhang, L. Qi, J. Huo, Y. Gao, J. Luo. Defensive Few-shot Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    • 2021
  • J. Huo, S. Jin, W. Li, J. Wu, Y.-K. Lai, Y. Shi, Y. Gao. “Manifold Alignment for Semantically Aligned Style Transfer.” International Conference on Computer Vision (ICCV), 2021.
  • L. Yang, Z. Wei, L. Qi, Y. Shi, Y. Gao. “Every Pixel Matters: Mining Latent Classes for Few-shot Segmentation.” International Conference on Computer Vision (ICCV), 2021.
  • Z. Gu, W. Li, J. Huo, L. Wang, Y. Gao. LoFGAN: Fusing Local Representations for Few-Shot Image Generation Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021.
  • H. Hou, J. Huo, J. Wu, Y.-K. Lai, Y. Gao. MW-GAN: Multi-Warping GAN for Caricature Generation With Multi-Style Geometric Exaggeration. IEEE Transactions on Image Processing (IEEE TIP), vol. 30, pp. 8644-8657, 2021.
  • Z. Gu, C. Dong, J. Huo, W. Li, Y. Gao. CariMe: Unpaired Caricature Generation with Multiple Exaggerations. IEEE Transactions on Multimedia, 2021.
    • 2020
  • P. Tian, Z. Wu, L. Qi, L. Wang, Y. Shi, Y. Gao. Differentiable Meta-learning Model for Few-shot Semantic Segmentation. In: AAAI Conference on Artificial Intelligence (AAAI'20), 2020.
  • X. Liu, W. Li, J. Huo, L. Yao, Y. Gao. Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio. In: AAAI Conference on Artificial Intelligence (AAAI'20), 2020.
  • Y. Liu, W. Wang, Y. Hu, J. Hao, X. Chen, Y. Gao. Multi-Agent Game Abstraction via Graph Neural Network. in Proc. 34th AAAI Conference on Artificial Intelligence (AAAI'20), 2020.
  • J. Xu, W. Li, X. Liu, D. Zhang, J. Liu, J. Han. Deep Embedded Complementary and Interactive Information for Multi-view Classification. In: AAAI Conference on Artificial Intelligence (AAAI'20), 2020.
  • W. Wang, T. Yang, Y. Liu, J. Hao, X. Hao, Y. Hu, Y. Chen, C. Fan, Y. Gao. From Few to More: Large-scale Dynamic Multiagent Curriculum Learning. In: Proc. 34th AAAI Conference on Artificial Intelligence (AAAI'20), 2020.
  • F. Shi, J. Wang, J. Shi, Z. Wu, Q. Wang, Z. Tang, K. He, Y. Shi, D. Shen. Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19. IEEE Reviews in Biomedical Engineering (RBME), 2020. (特邀综述).
  • W. Wang, T. Yang, Y. Liu, J. Hao, X. Hao, Y. Hu, Y. Chen, C. Fan, Y. Gao. Action Semantics Network: Considering the Effects of Actions in Multiagent Systems. In: International Conference on Learning Representations (ICLR), 2020.
  • C. Dong, W. Li, J. Huo, Z. Gu, Y. Gao. Learning Task-aware Local Representations for Few-Shot Learning. International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  • W. Li, L. Wang, J. Huo, Y. Shi, Y. Gao, J. Luo. Asymmetric Distribution Measure for Few-shot Learning. International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  • C. Shao, J. Huo, L. Qi, Z.-H. Feng, W. Li, C. Dong, Y. Gao. Biased Feature Learning for Occlusion Invariant Face Recognition. International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  • P. Tian, L. Qi, S. Dong, Y. Shi, Y. Gao. Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge. International Joint Conference on Artificial Intelligence (IJCAI), 2020.
    • 2019
  • W. Li, J. Xu, J. Huo, L. Wang, Y. Gao, J. Luo. Distribution Consistency based Covariance Metric Networks for Few-shot Learning. In: AAAI Conference on Artificial Intelligence (AAAI'19), 2019.
  • L. Lin, Q. Yu, J. Wen, Y. Gao. Feature-Selected and-Preserved Sampling for High-Dimensional Stream Data Summary[C]//2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019: 1406-1411.
  • Y. Zhuang, X. Chen, Y. Gao, Y. Hu. Accelerating Nash Q-Learning with Graphical Game Representation and Equilibrium Solving[C]//2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019: 939-946.
  • S. Dong, J. Chen, Y. Liu, T. Bao, Y. Gao. Reinforcement Learning from Algorithm Model to Industry Innovation: A Foundation Stone of Future Artificial Intelligence. TE Communications 17 (3), 31-41.
  • K. He, J. Huo, Y. Shi, Y. Gao, D. Shen. MIDCN: A Multiple Instance Deep Convolutional Network for Image Classification. Pacific Rim International Conference on Artificial Intelligence, 230-243.
  • W. Li, L. Wang, J. Xu, J. Huo, Y. Gao, J. Luo. Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning. CVPR, 2019.
  • L. Qi, L. Wang, J. Huo, L. Zhou, Y. Shi, Y. Gao. A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification. IEEE International Conference on Computer Vision (ICCV), 2019.
  • Y. Liu, Y. Hu, Y. Gao, Y. Chen, C. Fan. "Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns," in Proc. International Conference on Joint Artificial Intelligence (IJCAI) 2019.
  • Q. Yu, Y. Shi, J. Sun, Y. Gao, J. Zhu, Y. Dai. Crossbar-Net: A Novel Convolutional Neural Network for Kidney Tumor Segmentation in CT Images. IEEE Trans. on Image Processing (TIP), 2019.
    • 2018
  • Y. Lv, L. Qi, J. Huo, H. Wang, Y. Gao. Joint Multi-field Siamese Recurrent Neural Network for Entity Resolution[C]//Pacific Rim International Conference on Artificial Intelligence. Springer, Cham, 2018: 482-490.
    • 2017
  • Y. Shi, W. Li, Y. Gao, L. Cao, D. Shen. Beyond IID: Learning to Combine Non-IID Metrics for Vision Tasks. The 31st AAAI Conference on Artificial Intelligence (AAAI 2017).
  • L. Zhou, L. Wang, J. Zhang, Y. Shi, Y. Gao. Revisiting Distance Metric Learning for SPD Matrix based Visual Representation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017).
  • J. Sun, Y. Shi, Y. Gao, D. Shen. A Point Says A Lot: An Interactive Segmentation Method for MR Prostate Using One-Point Labeling. MICCAI-MLMI, 2017.
  • Y. Shi, W. Yang, Y. Gao, D. Shen. Does Manual Delineation Only Provide the Side Information in CT Prostate Segmentation? MICCAI 2017.
  • N. M. Kou, Y. Li, H. Wang, L. H. U, Z. Gong. Crowdsourced top-k queries by confidence-aware pairwise judgments. in: 2017 ACM SIGMOD International Conference on Management of Data (SIGMOD 2017).
    • 2016
  • S. Yang, Y. Gao, B. An, H. Wang, X. Chen. Efficient average reward reinforcement learning using constant shifting values. 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, February 2016.
  • J. Huo, Y. Gao, Y. Shi, W. Yang, H. Yin. Ensemble of Sparse Cross-Modal Metrics for Heterogeneous Face Recognition. ACM Multimedia, 2016.
    • 2015
  • L. Zhou, Q. Wang, L. Wang, Y. Shi. Machine Learning in Medical Imaging (Lecture Notes in Computer Science) (Eds.) Proceeding of MICCAI-MLMI 2015, Springer, LNCS 9352, 2015.
  • Y. Shi, Y. Gao, S. Liao, D. Zhang, Y. Gao, D. Shen. Semi-Automatic Segmentation of Prostate in CT Images via Spatial-Constrained Transductive Lasso. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2015, vol.37(11), p.2286-2303.
    • 2014
  • Y. Shi, H.-I. Suk, Y. Gao, D. Shen. Joint Coupled-Feature Representation and Coupled Boosting for Alzheimer's Disease Diagnosis. CVPR, 2014.
  • Y. Gao, Y. Shi, D. Shen. Interactive Prostate Segmentation based on Adaptive Feature Selection and Manifold Regularization Sanghyun Park. MICCAI-MLMI, 2014.
  • H. Wang, Y. Cai, Y. Yang, S. Zhang, N. Mamoulis. Durable queries over historical time series. IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(3): 595-607, 2014.
    • 2013
  • Y. Shi, S. Liao, Y. Gao, D. Zhang, Y. Gao, D. Shen. Prostate Segmentation in CT Images via Spatial-Constrained Transductive Lasso. CVPR, 2013.
    • 2009
  • W. Wang, T. Xu, Y. Gao, S. Lu. Probabilistic Seeking Prediction in P2P VoD Systems. Australasian Conference on Artificial Intelligence 2009: 676-685.
    • 2008
  • L. Shi, Y. Gao, L. Wu, S. Lin. Clustering with XCS on Complex Structure Dataset. Australasian Conference on Artificial Intelligence 2008: 489-499.
    • 2005
  • D. Cai, Z. Luo, K. Qian, Y. Gao. Towards Efficient Selection of Web Services with Reinforcement Learning Process. ictai, pp.372-376, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005.
  • C. Su, Y. Gao, S.-F. Chen, Z.-Q. Chen. The Study of Recognizing Options Based on SMDP. Pattern Recognition and Artificial Intelligence(PR & AI), Vol.18(6):679-684. (in Chinese).
    • 2004
  • Y. Pei, Y. Gao, Z. Chen, S. Chen. Believability Based Iterated Belief Revision. The 8th Pacific Rim International Conference on Artificial Intelligence. Trends in Artificial Intelligence: 8th Pacific Rim International Conference on Artificial Intelligence, Auckland, New Zealand, August 9-13, 2004. pp: 936-937.

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