30 citations · 30 across the 6 of their papers we have counts for
6 papers
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…
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…
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…