40 citations · 87 across the 23 of their papers we have counts for
24 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…
BioMedArena: An Open-source Toolkit for Building and Evaluating Biomedical Deep Research Agents
Jinge Wu, Hongjian Zhou, Mingde Zeng +8
Reproducing and comparing deep research agents today is hard: the same backbone evaluated on the same benchmark can report different accuracies across papers because the harness an…
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…
PresentBench: A Fine-Grained Rubric-Based Benchmark for Slide Generation
Xin-Sheng Chen, Jiayu Zhu, Pei-lin Li +3
Slides serve as a critical medium for conveying information in presentation-oriented scenarios such as academia, education, and business. Despite their importance, creating high-qu…
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…
Evo: Autoregressive-Diffusion Large Language Models with Evolving Balance
Junde Wu, Minhao Hu, Jiayuan Zhu +7
We introduce \textbf{Evo}, a duality latent trajectory model that bridges autoregressive (AR) and diffusion-based language generation within a continuous evolutionary generative fr…
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…
Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming
Jiazhen Pan, Bailiang Jian, Paul Hager +19
Large language models (LLMs) are increasingly used to answer health-related questions and support healthcare workflows, yet evidence for their safety still relies heavily on static…
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…
MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning
Jiazhen Pan, Che Liu, Junde Wu +6
Reasoning is a critical frontier for advancing medical image analysis, where transparency and trustworthiness play a central role in both clinician trust and regulatory approval. A…
RiskAgent: Synergizing Language Models with Validated Tools for Evidence-Based Risk Prediction
Fenglin Liu, Jinge Wu, Hongjian Zhou +9
Large Language Models (LLMs) achieve competitive results compared to human experts in medical examinations. However, it remains a challenge to apply LLMs to complex clinical decisi…
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…
Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Tools
Junde Wu, Jiayuan Zhu, Yuyuan Liu +2
We introduce Agentic Reasoning, a framework that enhances large language model (LLM) reasoning by integrating external tool-using agents. Agentic Reasoning dynamically leverages we…
SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation
Jiayuan Zhu, Junde Wu, Cheng Ouyang +2
Medical image segmentation data inherently contain uncertainty. This can stem from both imperfect image quality and variability in labeling preferences on ambiguous pixels, which d…
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…
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…
EpiGeoPop: A Tool for Developing Spatially Accurate Country-level Epidemiological Models
Lara Herriott, Henriette L. Capel, Isaac Ellmen +7
Mathematical models play a crucial role in understanding the spread of infectious disease outbreaks and influencing policy decisions. These models aid pandemic preparedness by pred…
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…
UGformer for Robust Left Atrium and Scar Segmentation Across Scanners
Tianyi Liu, Size Hou, Jiayuan Zhu +2
Thanks to the capacity for long-range dependencies and robustness to irregular shapes, vision transformers and deformable convolutions are emerging as powerful vision techniques of…