103 citations · 506 across the 54 of their papers we have counts for
55 papers
Fast Cross-Scenario Adaptation of CSI Models via Channel Conditional Parameter Generation
Xudong Zou, Siyu Wu, Zunlei Feng +4
Deep learning has shown strong potential for massive multiple-input multiple-output (Massive MIMO) physical-layer tasks, including channel state information (CSI) feedback and chan…
Adaptive Location Hierarchy Learning for Long-Tailed Mobility Prediction
Yu Wang, Junshu Dai, Yuchen Ying +4
Human mobility prediction is crucial for applications ranging from location-based recommendations to urban planning, which aims to forecast users' next location visits based on his…
SHAPE : Self-Improved Visual Preference Alignment by Iteratively Generating Holistic Winner
Kejia Chen, Jiawen Zhang, Jiacong Hu +4
Large Visual Language Models (LVLMs) increasingly rely on preference alignment to ensure reliability, which steers the model behavior via preference fine-tuning on preference data…
SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models
Jiawen Zhang, Kejia Chen, Zunlei Feng +4
With the growing popularity of LLMs among the general public users, privacy-preserving and adversarial robustness have become two pressing demands for LLM-based services, which hav…
Activation Approximations Can Incur Safety Vulnerabilities Even in Aligned LLMs: Comprehensive Analysis and Defense
Jiawen Zhang, Kejia Chen, Lipeng He +7
Large Language Models (LLMs) have showcased remarkable capabilities across various domains. Accompanying the evolving capabilities and expanding deployment scenarios of LLMs, their…
SEW: Self-calibration Enhanced Whole Slide Pathology Image Analysis
Haoming Luo, Xiaotian Yu, Shengxuming Zhang +8
Pathology images are considered the ``gold standard" for cancer diagnosis and treatment, with gigapixel images providing extensive tissue and cellular information. Existing methods…
Deep Feature Response Discriminative Calibration
Wenxiang Xu, Tian Qiu, Linyun Zhou +3
Deep neural networks (DNNs) have numerous applications across various domains. Several optimization techniques, such as ResNet and SENet, have been proposed to improve model accura…
A Large-scale Universal Evaluation Benchmark For Face Forgery Detection
Yijun Bei, Hengrui Lou, Jinsong Geng +5
With the rapid development of AI-generated content (AIGC) technology, the production of realistic fake facial images and videos that deceive human visual perception has become poss…
Improving Adversarial Robustness via Feature Pattern Consistency Constraint
Jiacong Hu, Jingwen Ye, Zunlei Feng +5
Convolutional Neural Networks (CNNs) are well-known for their vulnerability to adversarial attacks, posing significant security concerns. In response to these threats, various defe…
A Comprehensive Study of Structural Pruning for Vision Models
Changhao Li, Haoling Li, Mengqi Xue +6
Structural pruning has emerged as a promising approach for producing more efficient models. Nevertheless, the community suffers from a lack of standardized benchmarks and metrics,…
Angle Robustness Unmanned Aerial Vehicle Navigation in GNSS-Denied Scenarios
Yuxin Wang, Zunlei Feng, Haofei Zhang +4
Due to the inability to receive signals from the Global Navigation Satellite System (GNSS) in extreme conditions, achieving accurate and robust navigation for Unmanned Aerial Vehic…
Progressive Feature Self-reinforcement for Weakly Supervised Semantic Segmentation
Jingxuan He, Lechao Cheng, Chaowei Fang +3
Compared to conventional semantic segmentation with pixel-level supervision, Weakly Supervised Semantic Segmentation (WSSS) with image-level labels poses the challenge that it alwa…
Graph Neural Networks-based Hybrid Framework For Predicting Particle Crushing Strength
Tongya Zheng, Tianli Zhang, Qingzheng Guan +4
Graph Neural Networks have emerged as an effective machine learning tool for multi-disciplinary tasks such as pharmaceutical molecule classification and chemical reaction predictio…
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization
Kaixuan Chen, Shunyu Liu, Tongtian Zhu +5
Graph Neural Networks (GNNs) have emerged as a powerful category of learning architecture for handling graph-structured data. However, existing GNNs typically ignore crucial struct…
AFPN: Asymptotic Feature Pyramid Network for Object Detection
Guoyu Yang, Jie Lei, Zhikuan Zhu +3
Multi-scale features are of great importance in encoding objects with scale variance in object detection tasks. A common strategy for multi-scale feature extraction is adopting the…
Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulation
Yu Wang, Tongya Zheng, Shunyu Liu +4
Human mobility patterns have shown significant applications in policy-decision scenarios and economic behavior researches. The human mobility simulation task aims to generate human…
Improving Knowledge Distillation via Regularizing Feature Norm and Direction
Yuzhu Wang, Lechao Cheng, Manni Duan +3
Knowledge distillation (KD) exploits a large well-trained model (i.e., teacher) to train a small student model on the same dataset for the same task. Treating teacher features as k…
ViT-Calibrator: Decision Stream Calibration for Vision Transformer
Lin Chen, Zhijie Jia, Tian Qiu +4
A surge of interest has emerged in utilizing Transformers in diverse vision tasks owing to its formidable performance. However, existing approaches primarily focus on optimizing in…
Temporal Aggregation and Propagation Graph Neural Networks for Dynamic Representation
Tongya Zheng, Xinchao Wang, Zunlei Feng +6
Temporal graphs exhibit dynamic interactions between nodes over continuous time, whose topologies evolve with time elapsing. The whole temporal neighborhood of nodes reveals the va…
Transition Propagation Graph Neural Networks for Temporal Networks
Tongya Zheng, Zunlei Feng, Tianli Zhang +6
Researchers of temporal networks (e.g., social networks and transaction networks) have been interested in mining dynamic patterns of nodes from their diverse interactions. Inspired…
Life Regression based Patch Slimming for Vision Transformers
Jiawei Chen, Lin Chen, Jiang Yang +4
Vision transformers have achieved remarkable success in computer vision tasks by using multi-head self-attention modules to capture long-range dependencies within images. However,…
Propheter: Prophetic Teacher Guided Long-Tailed Distribution Learning
Wenxiang Xu, Yongcheng Jing, Linyun Zhou +4
The problem of deep long-tailed learning, a prevalent challenge in the realm of generic visual recognition, persists in a multitude of real-world applications. To tackle the heavil…
Team DETR: Guide Queries as a Professional Team in Detection Transformers
Tian Qiu, Linyun Zhou, Wenxiang Xu +3
Recent proposed DETR variants have made tremendous progress in various scenarios due to their streamlined processes and remarkable performance. However, the learned queries usually…
Model Doctor for Diagnosing and Treating Segmentation Error
Zhijie Jia, Lin Chen, Kaiwen Hu +3
Despite the remarkable progress in semantic segmentation tasks with the advancement of deep neural networks, existing U-shaped hierarchical typical segmentation networks still suff…