33 citations · 53 across the 33 of their papers we have counts for
34 papers
SQuaD-SQL: Efficient Text-to-SQL with Small Language Models via LLM-Guided Knowledge Distillation
Wangyu Wu, Xiaojian Lin, Rong Fu +4
Text-to-SQL is a fundamental task in natural language processing that enables users to interact with structured databases using natural language. While large language models (LLMs)…
TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media
Fuchen Zheng, Chengpei Xu, Long Ma +10
Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical issues: axis-biased scan orde…
Intrinsic Concept Extraction Based on Compositional Interpretability
Hanyu Shi, Hong Tao, Guoheng Huang +5
Unsupervised Concept Extraction aims to extract concepts from a single image; however, existing methods suffer from the inability to extract composable intrinsic concepts. To addre…
ChordEdit: One-Step Low-Energy Transport for Image Editing
Liangsi Lu, Xuhang Chen, Minzhe Guo +3
The advent of one-step text-to-image (T2I) models offers unprecedented synthesis speed. However, their application to text-guided image editing remains severely hampered, as forcin…
RGA-Net: A Vision Enhancement Framework for Robotic Surgical Systems Using Reciprocal Attention Mechanisms
Quanjun Li, Weixuan Li, Han Xia +3
Robotic surgical systems rely heavily on high-quality visual feedback for precise teleoperation; yet, surgical smoke from energy-based devices significantly degrades endoscopic vid…
Context Tokens are Anchors: Understanding the Repetition Curse in dMLLMs from an Information Flow Perspective
Qiyan Zhao, Xiaofeng Zhang, Shuochen Chang +7
Recent diffusion-based Multimodal Large Language Models (dMLLMs) suffer from high inference latency and therefore rely on caching techniques to accelerate decoding. However, the ap…
HBFormer: A Hybrid-Bridge Transformer for Microtumor and Miniature Organ Segmentation
Fuchen Zheng, Xinyi Chen, Weixuan Li +6
Medical image segmentation is a cornerstone of modern clinical diagnostics. While Vision Transformers that leverage shifted window-based self-attention have established new benchma…
Tag-Enriched Multi-Attention with Large Language Models for Cross-Domain Sequential Recommendation
Wangyu Wu, Xuhang Chen, Zhenhong Chen +5
Cross-Domain Sequential Recommendation (CDSR) plays a crucial role in modern consumer electronics and e-commerce platforms, where users interact with diverse services such as books…
UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis
Zhuo Li, Xuhang Chen, Shuqiang Wang +3
Functional ultrasound (fUS) is a neuroimaging technique known for its high spatiotemporal resolution, enabling non-invasive observation of brain activity through neurovascular coup…
Empowering Functional Neuroimaging: A Pre-trained Generative Framework for Unified Representation of Neural Signals
Weiheng Yao, Xuhang Chen, Shuqiang Wang
Multimodal functional neuroimaging enables systematic analysis of brain mechanisms and provides discriminative representations for brain-computer interface (BCI) decoding. However,…
ConnectomeDiffuser: Generative AI Enables Brain Network Construction from Diffusion Tensor Imaging
Xuhang Chen, Michael Kwok-Po Ng, Kim-Fung Tsang +2
Brain network analysis plays a crucial role in diagnosing and monitoring neurodegenerative disorders such as Alzheimer's disease (AD). Existing approaches for constructing structur…
High-Fidelity Functional Ultrasound Reconstruction via A Visual Auto-Regressive Framework
Xuhang Chen, Zhuo Li, Yanyan Shen +4
Functional ultrasound (fUS) imaging provides exceptional spatiotemporal resolution for neurovascular mapping, yet its practical application is significantly hampered by critical ch…
Underwater Image Restoration Through a Prior Guided Hybrid Sense Approach and Extensive Benchmark Analysis
Xiaojiao Guo, Xuhang Chen, Shuqiang Wang +1
Underwater imaging grapples with challenges from light-water interactions, leading to color distortions and reduced clarity. In response to these challenges, we propose a novel Col…
Layer-Wise Feature Metric of Semantic-Pixel Matching for Few-Shot Learning
Hao Tang, Junhao Lu, Guoheng Huang +5
In Few-Shot Learning (FSL), traditional metric-based approaches often rely on global metrics to compute similarity. However, in natural scenes, the spatial arrangement of key insta…
IMAN: An Adaptive Network for Robust NPC Mortality Prediction with Missing Modalities
Yejing Huo, Guoheng Huang, Lianglun Cheng +5
Accurate prediction of mortality in nasopharyngeal carcinoma (NPC), a complex malignancy particularly challenging in advanced stages, is crucial for optimizing treatment strategies…
TAGE: Trustworthy Attribute Group Editing for Stable Few-shot Image Generation
Ruicheng Zhang, Guoheng Huang, Yejing Huo +4
Generative Adversarial Networks (GANs) have emerged as a prominent research focus for image editing tasks, leveraging the powerful image generation capabilities of the GAN framewor…
Test-Time Intensity Consistency Adaptation for Shadow Detection
Leyi Zhu, Weihuang Liu, Xinyi Chen +4
Shadow detection is crucial for accurate scene understanding in computer vision, yet it is challenged by the diverse appearances of shadows caused by variations in illumination, ob…
Lagrange Duality and Compound Multi-Attention Transformer for Semi-Supervised Medical Image Segmentation
Fuchen Zheng, Quanjun Li, Weixuan Li +5
Medical image segmentation, a critical application of semantic segmentation in healthcare, has seen significant advancements through specialized computer vision techniques. While d…
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ Segmentation
Fuchen Zheng, Xinyi Chen, Xuhang Chen +5
Medical image segmentation, a crucial task in computer vision, facilitates the automated delineation of anatomical structures and pathologies, supporting clinicians in diagnosis, t…
SMAFormer: Synergistic Multi-Attention Transformer for Medical Image Segmentation
Fuchen Zheng, Xuhang Chen, Weihuang Liu +5
In medical image segmentation, specialized computer vision techniques, notably transformers grounded in attention mechanisms and residual networks employing skip connections, have…
Dual-Hybrid Attention Network for Specular Highlight Removal
Xiaojiao Guo, Xuhang Chen, Shenghong Luo +2
Specular highlight removal plays a pivotal role in multimedia applications, as it enhances the quality and interpretability of images and videos, ultimately improving the performan…
MFDNet: Multi-Frequency Deflare Network for Efficient Nighttime Flare Removal
Yiguo Jiang, Xuhang Chen, Chi-Man Pun +2
When light is scattered or reflected accidentally in the lens, flare artifacts may appear in the captured photos, affecting the photos' visual quality. The main challenge in flare…
Multi-modal Mood Reader: Pre-trained Model Empowers Cross-Subject Emotion Recognition
Yihang Dong, Xuhang Chen, Yanyan Shen +3
Emotion recognition based on Electroencephalography (EEG) has gained significant attention and diversified development in fields such as neural signal processing and affective comp…
Adaptive Query Prompting for Multi-Domain Landmark Detection
Yuhui Li, Qiusen Wei, Guoheng Huang +5
Medical landmark detection is crucial in various medical imaging modalities and procedures. Although deep learning-based methods have achieve promising performance, they are mostly…