3 citations · 8 across the 4 of their papers we have counts for
4 papers
CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology
Yuxuan Sun, Yixuan Si, Chenglu Zhu +7
The emergence of large multimodal models (LMMs) has brought significant advancements to pathology. Previous research has primarily focused on separately training patch-level and wh…
PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration
Yuxuan Sun, Yunlong Zhang, Yixuan Si +7
Vision Language Models (VLMs) like CLIP have attracted substantial attention in pathology, serving as backbones for applications such as zero-shot image classification and Whole Sl…
PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology
Yuxuan Sun, Hao Wu, Chenglu Zhu +11
The emergence of large multimodal models has unlocked remarkable potential in AI, particularly in pathology. However, the lack of specialized, high-quality benchmark impeded their…
Multimodal Question Answering for Unified Information Extraction
Yuxuan Sun, Kai Zhang, Yu Su
Multimodal information extraction (MIE) aims to extract structured information from unstructured multimedia content. Due to the diversity of tasks and settings, most current MIE mo…