1 citations · 1 across the 14 of their papers we have counts for
17 papers
VoxelSage: Tool-Augmented 3D CT Analysis and Simulator-Shielded Sequential Resection Planning for Liver Tumors
Binghong Qian, Xuanhe Liu, Yifan Xing +3
Preoperative liver-tumor assessment requires segmentation, physical-space measurement, visual evidence, and resection planning from the same three-dimensional CT volume. Existing t…
SeVeR: Selective Visual Exposure and Retrieval for 3D Medical Image Question Answering
Yaojun Hu, Danyang Tu, Yang Liu +8
Volumetric medical VQA requires reasoning over long and redundant 3D visual token sequences, especially in multi-sequence MRI where complementary modalities provide diverse diagnos…
D3O: Dynamic Distribution Distillation for Ordinal Regression
Chunlai Dong, Yaojun Hu, Yuyang Xu +2
Ordinal regression is widely used in scenarios where labels are discrete yet inherently ordered. In practice, however, ordinal labels are often obtained by discretizing underlying…
A Scale-adaptive Vision Model Links C. elegans Neuronal Morphology to Behavior for Neurotoxicity Assessment
Haochao Ying, Shenchong Lv, Yutao Sun +8
Neurological disorders are a leading cause of global disability and are increasingly linked to environmental chemical exposures. Yet neurotoxicity assessment still relies on hand-s…
HyperVLP: Enhancing Hierarchical Surgical Video-Language Pre-training in Hyperbolic Space
Yaojun Hu, Kun Yuan, Nassir Navab +3
Surgical vision-language foundation models typically adopt educational materials, such as surgical lecture videos, to transfer surgical knowledge encoded in language into visual re…
HDMoE: A Hierarchical Decoupling-Fusion Mixture-of-Experts Framework for Multimodal Cancer Survival Prediction
Huayi Wang, Haochao Ying, Yuyang Xu +5
Multimodal survival prediction, a crucial yet challenging task, demands the integration of multimodal medical data (\eg Whole Slide Images (WSIs) and Genomic Profiles) to achieve a…
Versatile and Risk-Sensitive Cardiac Diagnosis via Graph-Based ECG Signal Representation
Yue Wang, Yuyang Xu, Renjun Hu +7
Despite the rapid advancements of electrocardiogram (ECG) signal diagnosis and analysis methods through deep learning, two major hurdles still limit their clinical adoption: the la…
Enabling Agents to Communicate Entirely in Latent Space
Zhuoyun Du, Runze Wang, Huiyu Bai +6
While natural language is the de facto communication medium for LLM-based agents, it presents a fundamental constraint. The process of downsampling rich, internal latent states int…
SSPO: Self-traced Step-wise Preference Optimization for Process Supervision and Reasoning Compression
Yuyang Xu, Yi Cheng, Haochao Ying +5
Test-time scaling has proven effective in further enhancing the performance of pretrained Large Language Models (LLMs). However, mainstream post-training methods (i.e., reinforceme…
RCM-ACT: Imitation Learning with Dynamic RCM Calibration for Autonomous Intraocular Foreign Body Removal
Yue Wang, Wenjie Deng, Haotian Xue +5
Intraocular foreign body removal demands millimeter-level precision in confined intraocular spaces, yet existing robotic systems predominantly rely on manual teleoperation with ste…
Decouple, Reorganize, and Fuse: A Multimodal Framework for Cancer Survival Prediction
Huayi Wang, Haochao Ying, Yuyang Xu +5
Cancer survival analysis commonly integrates information across diverse medical modalities to make survival-time predictions. Existing methods primarily focus on extracting differe…
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset
Jinhong Wang, Shuo Tong, Jian liu +6
Visual rating is an essential capability of artificial intelligence (AI) for multi-dimensional quantification of visual content, primarily applied in ordinal regression (OR) tasks…
Dual-level Fuzzy Learning with Patch Guidance for Image Ordinal Regression
Chunlai Dong, Haochao Ying, Qibo Qiu +3
Ordinal regression bridges regression and classification by assigning objects to ordered classes. While human experts rely on discriminative patch-level features for decisions, cur…
Uncertainty-Aware Multi-Expert Knowledge Distillation for Imbalanced Disease Grading
Shuo Tong, Shangde Gao, Ke Liu +4
Automatic disease image grading is a significant application of artificial intelligence for healthcare, enabling faster and more accurate patient assessments. However, domain shift…
Large Language Models Could Be Rote Learners
Yuyang Xu, Renjun Hu, Haochao Ying +3
Benchmark-based evaluation, e.g., multiple-choice questions (MCQs) and open-ended questions (OEQs), is widely used for evaluating Large Language Models (LLMs), yet their reliabilit…
AnyECG: Foundational Models for Multitask Cardiac Analysis in Real-World Settings
Yue Wang, Xu Cao, Yaojun Hu +7
Electrocardiogram (ECG), a non-invasive and affordable tool for cardiac monitoring, is highly sensitive in detecting acute heart attacks. However, due to the lengthy nature of ECG…
Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge
Kendall Schmidt, Benjamin Bearce, Ken Chang +21
The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due t…