Publications (17)
StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors
Qinkai Yu, Chong Zhang, Gaojie Jin +11
Annotating medical data for training AI models is often costly and limited due to the shortage of specialists with relevant clinical expertise. This challenge is further compounded…
Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models
Qingcheng Zeng, Mingyu Jin, Qinkai Yu +12
Large Language Models (LLMs) are employed across various high-stakes domains, where the reliability of their outputs is crucial. One commonly used method to assess the reliability…
Disentangled Fine-Grained Prototype Learning for Incomplete Image-Tabular Classification
Feixiang Zhou, Jianyang Xie, Zhuangzhi Gao +10
The missing-modality problem poses a significant challenge in image-tabular multimodal learning across a wide range of multimedia applications, including product understanding, rec…
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System
Qinkai Yu, Mingyu Jin, Dong Shu +8
Recent advancements in artificial intelligence (AI), especially large language models (LLMs), have significantly advanced healthcare applications and demonstrated potentials in int…
A Simple and Effective Baseline for Attentional Generative Adversarial Networks
Mingyu Jin, Chong Zhang, Qinkai Yu +3
Synthesising a text-to-image model of high-quality images by guiding the generative model through the Text description is an innovative and challenging task. In recent years, AttnG…
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities
Hua Tang, Chong Zhang, Mingyu Jin +5
Large language models (LLMs) have been applied in many fields and have developed rapidly in recent years. As a classic machine learning task, time series forecasting has recently b…
CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting
Qinkai Yu, Jianyang Xie, Anh Nguyen +6
Diabetic retinopathy (DR) is a complication of diabetes and usually takes decades to reach sight-threatening levels. Accurate and robust detection of DR severity is critical for th…
RetiBridge: Bridging Quantitative Retinal Biomarkers and Qualitative Diagnosis with a Knowledge-Guided Multimodal Large Language Model
Zhuangzhi Gao, Hongyi Qin, He Zhao +10
Retinal biomarkers captured by color fundus photography and optical coherence tomography provide clinically valuable evidence for both ocular and systemic diseases. Multimodal larg…
RealRoute: Dynamic Query Routing System via Retrieve-then-Verify Paradigm
Jiahe Liu, Qinkai Yu, Jingcheng Niu +5
Despite the success of Retrieval-Augmented Generation (RAG) in grounding LLMs with external knowledge, its application over heterogeneous sources (e.g., private databases, global c…
Goal-guided Generative Prompt Injection Attack on Large Language Models
Chong Zhang, Mingyu Jin, Qinkai Yu +3
Current large language models (LLMs) provide a strong foundation for large-scale user-oriented natural language tasks. A large number of users can easily inject adversarial text or…
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?
Mingyu Jin, Qinkai Yu, Jingyuan Huang +10
Large language models (LLMs) have shown remarkable performances across a wide range of tasks. However, the mechanisms by which these models encode tasks of varying complexities rem…
Leveraging Persistence Image to Enhance Robustness and Performance in Curvilinear Structure Segmentation
Zhuangzhi Gao, Feixiang Zhou, He Zhao +8
Segmenting curvilinear structures in medical images is essential for analyzing morphological patterns in clinical applications. Integrating topological properties, such as connecti…
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers
Meng Wang, Tian Lin, Qingshan Hou +37
Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied across different clinical settings,…
Parameterized Diffusion Optimization enabled Autoregressive Ordinal Regression for Diabetic Retinopathy Grading
Qinkai Yu, Wei Zhou, Hantao Liu +7
As a long-term complication of diabetes, diabetic retinopathy (DR) progresses slowly, potentially taking years to threaten vision. An accurate and robust evaluation of its severity…
Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transport
Qinkai Yu, Jianyang Xie, Yitian Zhao +7
Multimodal ophthalmic imaging-based diagnosis integrates color fundus image with optical coherence tomography (OCT) to provide a comprehensive view of ocular pathologies. However,…
The Impact of Reasoning Step Length on Large Language Models
Mingyu Jin, Qinkai Yu, Dong Shu +5
Chain of Thought (CoT) is significant in improving the reasoning abilities of large language models (LLMs). However, the correlation between the effectiveness of CoT and the length…
Bridging the Projection Gap: Overcoming Projection Bias Through Parameterized Distance Learning
Chong Zhang, Mingyu Jin, Qinkai Yu +3
Generalized zero-shot learning (GZSL) aims to recognize samples from both seen and unseen classes using only seen class samples for training. However, GZSL methods are prone to bia…