Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileAcademic lineage
Possible advisorsa guess from early papers, not confirmed
- Xiaowei XuSuggested from co-authorship
Is this you? Claim this profile to confirm or dismiss it.
Works91 from public data
- Federated Class-Incremental Learning327
A novel Global-Local Forgetting Compensation (GLFC) model is developed, to learn a global class-incremental model for alleviating the catastrophic forgetting from both local and global perspectives, and a prototype gradient-based communication mechanism is developed to protect the privacy.
- From System 1 to System 2: A Survey of Reasoning Large Language Models314
This survey provides an overview of the progress in foundational LLMs and the early development of System 2 technologies, exploring how their combination has paved the way for reasoning LLMs and explores promising directions for advancing reasoning LLMs.
- Data Poisoning Attacks on Federated Machine Learning310
This work attempts to attacking a popular federated multitask learning framework, which uses a general multitask learning framework to handle statistical challenges in the federated learning setting, and proposes a novel systems-aware optimization method, called as attack on federated learning (AT2FL), to efficiently derive the implicit gradients for poisoned data, and further attain optimal attack strategies in the federated machine learning.
- 248
- 154
- What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation150
A new unsupervised semantic transfer model including two complementary modules for endoscopic lesions segmentation, which can alternatively determine where and how to explore transferable domain-invariant knowledge between labeled source lesions dataset and unlabeled target diseases dataset is developed.
- BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM121
The proposed BoW3D builds the bag of words based on the 3D LiDAR feature LinK3D, which is efficient, pose-invariant and can be used for accurate point-to-point matching and shows better performance in terms of max and extended precision scores on most scenes.
- 117
- 106
- No One Left Behind: Real-World Federated Class-Incremental Learning102
A proxy server is designed to tackle global forgetting caused by Non-IID class imbalance between different clients, and a category-balanced gradient-adaptive compensation loss and a category gradient-induced semantic distillation loss are developed.
- Exploring the Equivalence of Siamese Self-Supervised Learning via A Unified Gradient Framework74
UniGrad is proposed, a simple but effective gradient form for self-supervised learning that does not require a memory bank or a predictor network, but can still achieve state-of-the-art performance and easily adopt other training strategies.
- Xformer: Hybrid X-Shaped Transformer for Image Denoising73
A hybrid X-shaped vision Transformer, named Xformer, which performs notably on image denoising tasks, and proposes the Bidirectional Connection Unit (BCU) to couple the learned representations from these two branches while providing enhanced information fusion.
- Federated Incremental Semantic Segmentation71
A Forgetting-Balanced Learning (FBL) model is proposed to address heterogeneous forgetting on old classes from both intra-client and interclient aspects to address catastrophic forgetting in Federated learning-based semantic segmentation.
- LinK3D: Linear Keypoints Representation for 3D LiDAR Point Cloud67
A novel 3D feature representation method that fully considers the characteristics (such as the sparsity and complexity) of LiDAR point clouds and represents the keypoint with its robust neighbor keypoints, which provides strong constraints in the description of the keypoint.
- Create Your World: Lifelong Text-to-Image Diffusion66
A model which intends to overcome knowledge “catastrophic forgetting” for the past encountered concepts, and semantic “catastrophic neglecting” for one or more concepts in the text prompt is proposed.
- 51
- Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation50
A pseudo label generator is proposed to leverage seed information to generate highly-confident pseudo pixel labels by incorporating class balance and super-pixel spatial prior in a new semantic lesions representation transfer model for weakly-supervised endoscopic lesions segmentation.
- CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation47
A critical transfer based adversarial framework is designed to highlight transferable domain-wise knowledge while neglecting untransferable knowledge, and a symmetric soft divergence loss is presented to explore inter-class relationships and facilitate category-wise distribution alignment.
- Weakly-Supervised Cross-Domain Adaptation for Endoscopic Lesions Segmentation45
A new weakly-supervised lesions transfer framework is proposed, which can not only explore transferable domain-invariant knowledge across different datasets, but also prevent the negative transfer of untransferable representations.
- I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting42
A new Incremental 3D Object Learning (i.e., I3DOL) model is proposed, which is the first exploration to learn new classes of 3D object continually, and an adaptive-geometric centroid module is designed to construct discriminative local geometric structures, which can better characterize the irregular point cloud representation for3D object.
- 40
- 40
- Lifelong robotic visual-tactile perception learning38
A new L ifelong V isual- T actile L earning (LVTL) model is proposed for continuous robotic visual-tactile perception tasks, which fully explores the latent correlations in both intra- modality and cross-modality aspects.
- 36
- Gradient-Semantic Compensation for Incremental Semantic Segmentation35
A step-aware gradient compensation that can balance forgetting paces of previously seen classes by re-weighting gradient back-propagation is developed and a soft-sharp semantic relation distillation is proposed to distill consistent inter-class semantic relations via soft labels for alleviating catastrophic forgetting from the semantic aspect.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.