1 citations · 1 across the 6 of their papers we have counts for
7 papers
Syndrome, Synergy, and Safety: Structured Reasoning and Knowledge-Driven Alignment for TCM Prescription Generation
Zheng Chen, ZhiCheng Du, Haoxuan Li +1
Applying large language models to Traditional Chinese Medicine (TCM) prescription generation reveals three clinically critical gaps: models produce end-to-end mappings without audi…
LingLan: An Advancing Traditional Chinese Medicine Diagnosis LLM with Multimodal Data
Zheng Chen, Zhicheng Du, Haoxuan Li +2
Though artificial intelligence (AI) increasingly transforms modern medicine, its integration into Traditional Chinese Medicine (TCM) has been relatively slow, primarily due to TCM'…
TCMaster: Confidence-Aware Querying and Workload-Guided Physical Design for Multi-Source Traditional Chinese Medicine Knowledge Graphs
Zheng Chen, Yuzhu Li, Haoxuan Li +3
Multi-source knowledge graphs (KGs) need query mechanisms that expose reliability and exploit domain structure. This paper presents TCMaster, a property-graph query substrate for c…
Beyond Function-Level Search: Repository-Aware Dual-Encoder Code Retrieval with Adversarial Verification
Aofan Liu, Shiyuan Song, Haoxuan Li +2
The escalating complexity of modern codebases has intensified the need for retrieval systems capable of interpreting cross-component change intents, a capability fundamentally abse…
AdaDocVQA: Adaptive Framework for Long Document Visual Question Answering in Low-Resource Settings
Haoxuan Li, Wei Song, Aofan Liu +1
Document Visual Question Answering (Document VQA) faces significant challenges when processing long documents in low-resource environments due to context limitations and insufficie…
DBF-UNet: A Two-Stage Framework for Carotid Artery Segmentation with Pseudo-Label Generation
Haoxuan Li, Wei Song, Aofan Liu +1
Medical image analysis faces significant challenges due to limited annotation data, particularly in three-dimensional carotid artery segmentation tasks, where existing datasets exh…
HCMA-UNet: A Hybrid CNN-Mamba UNet with Axial Self-Attention for Efficient Breast Cancer Segmentation
Haoxuan Li, Wei song, Peiwu Qin +2
Breast cancer lesion segmentation in DCE-MRI remains challenging due to heterogeneous tumor morphology and indistinct boundaries. To address these challenges, this study proposes a…