40 citations · 87 across the 20 of their papers we have counts for
21 papers
MedRSI: Recursive Self-Improvement for Medical Agents via Clinically Aligned Self-Evolution
Junde Wu, Jiayuan Zhu, Minghao Hu +2
Medical agents increasingly combine general reasoning models with specialized clinical tools, yet their capabilities remain largely fixed by what clinicians and engineers design be…
AI Can Be Easily Persuaded in Clinical Decision Making
Jiayuan Zhu, Jiazhen Pan, Fenglin Liu +2
As AI becomes increasingly integrated into clinical practice, it is playing a growing role in medical decision making. Medicine, however, is a high stakes and evidence based field,…
J-CoT: Chain-of-Thought in J-Space
Junde Wu, Jiayuan Zhu, Fengling Liu +2
Chain-of-thought prompting improves language-model reasoning by carrying intermediate states across successive computation steps. However, relying on natural language as the only r…
From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding
Yuyuan Liu, Yiping Ji, Anjie Le +6
Finetuning Large Vision-Language Models with reinforcement learning has emerged as a promising approach to enhance their capability in object-level grounding. However, existing met…
3DMedAgent: Unified Perception-to-Understanding for 3D Medical Analysis
Ziyue Wang, Linghan Cai, Chang Han Low +8
3D CT analysis spans a continuum from low-level perception to high-level clinical understanding. Existing 3D-oriented analysis methods adopt either isolated task-specific modeling…
MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows
Weixiang Shen, Chengzhi Shen, Yanzhu Hu +12
Medical imaging benchmarks often evaluate VLMs on pre-selected 2D images, slices, crops, or patches, making evaluation closer to visual recognition. Real clinical workflows impose…
SWE Context Bench: A Benchmark for Context Learning in Coding
Jiayuan Zhu, Junde Wu, Minhao Hu +9
Large language models are increasingly used as coding agents for software engineering tasks. Current benchmarks mainly evaluate whether the agent can correctly solve the request or…
Git Context Controller: Manage the Context of LLM-based Agents like Git
Junde Wu, Minhao Hu, Jiayuan Zhu +4
Large language model (LLM) agents have demonstrated strong capabilities in long-horizon tasks by interleaving reasoning with tool use. However, as these agents scale to complex wor…
Structure Matters: Revisiting Boundary Refinement in Video Object Segmentation
Guanyi Qin, Ziyue Wang, Daiyun Shen +5
Given an object mask, Semi-supervised Video Object Segmentation (SVOS) technique aims to track and segment the object across video frames, serving as a fundamental task in computer…
SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence
Zhitao Zeng, Zhu Zhuo, Xiaojun Jia +12
Foundation models have achieved transformative success across biomedical domains by enabling holistic understanding of multimodal data. However, their application in surgery remain…
ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking
Haofeng Liu, Mingqi Gao, Xuxiao Luo +4
Surgical scene segmentation is critical in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, referring surgical segmentation is…
MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflow
Ziyue Wang, Junde Wu, Linghan Cai +4
In modern medicine, clinical diagnosis relies on the comprehensive analysis of primarily textual and visual data, drawing on medical expertise to ensure systematic and rigorous rea…
Ask Patients with Patience: Enabling LLMs for Human-Centric Medical Dialogue with Grounded Reasoning
Jiayuan Zhu, Jiazhen Pan, Yuyuan Liu +2
The severe shortage of medical doctors limits access to timely and reliable healthcare, leaving millions underserved. Large language models (LLMs) offer a potential solution but st…
MedUHIP: Towards Human-In-the-Loop Medical Segmentation
Jiayuan Zhu, Junde Wu
Although segmenting natural images has shown impressive performance, these techniques cannot be directly applied to medical image segmentation. Medical image segmentation is partic…
Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
Haofeng Liu, Erli Zhang, Junde Wu +2
Surgical video segmentation is a critical task in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, the Segment Anything Model 2…
Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation
Junde Wu, Jiayuan Zhu, Yunli Qi +4
We introduce a novel graph-based Retrieval-Augmented Generation (RAG) framework specifically designed for the medical domain, called \textbf{MedGraphRAG}, aimed at enhancing Large…
Medical SAM 2: Segment medical images as video via Segment Anything Model 2
Jiayuan Zhu, Abdullah Hamdi, Yunli Qi +2
Medical image segmentation plays a pivotal role in clinical diagnostics and treatment planning, yet existing models often face challenges in generalization and in handling both 2D…
MGI: Multimodal Contrastive pre-training of Genomic and Medical Imaging
Jiaying Zhou, Mingzhou Jiang, Junde Wu +3
Medicine is inherently a multimodal discipline. Medical images can reflect the pathological changes of cancer and tumors, while the expression of specific genes can influence their…
Not just Birds and Cars: Generic, Scalable and Explainable Models for Professional Visual Recognition
Junde Wu, Jiayuan Zhu, Min Xu +1
Some visual recognition tasks are more challenging then the general ones as they require professional categories of images. The previous efforts, like fine-grained vision classific…
Towards Collective Intelligence: Uncertainty-aware SAM Adaptation for Ambiguous Medical Image Segmentation
Mingzhou Jiang, Jiaying Zhou, Junde Wu +3
Collective intelligence from multiple medical experts consistently surpasses individual expertise in clinical diagnosis, particularly for ambiguous medical image segmentation tasks…
One-Prompt to Segment All Medical Images
Junde Wu, Jiayuan Zhu, Yueming Jin +1
Large foundation models, known for their strong zero-shot generalization, have excelled in visual and language applications. However, applying them to medical image segmentation, a…