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Xiaoman Zhang

Harvard University

22 papers hereh-index 203.1k citations39 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author16

Across the 21 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CV16
  • cs.CL3
  • eess.IV3
affiliations
  • Harvard University
Homepage
same name
  • Xiaoman Zhang — 17 papers, h 7
  • Xiaoman Zhang — 2 papers
  • Xiaoman Zhang — 1 paper, h 4
  • Xiaoman Zhang — 1 paper, h 1
  • Xiaoman Zhang — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202026
most citedPMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

60 citations · 268 across the 22 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

eess.IV2024★ 2 cited

AutoRG-Brain: Grounded Report Generation for Brain MRI

Jiayu Lei, Xiaoman Zhang, Chaoyi Wu +6

Radiologists are tasked with interpreting a large number of images in a daily base, with the responsibility of generating corresponding reports. This demanding workload elevates th…

cs.CV2024★ 5 cited

RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis

Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4

Developing generalist foundation model has recently attracted tremendous attention among researchers in the field of AI for Medicine (AI4Medicine). A pivotal insight in developing…

cs.CV2024★ 1 cited

Knowledge-enhanced Visual-Language Pretraining for Computational Pathology

Xiao Zhou, Xiaoman Zhang, Chaoyi Wu +3

In this paper, we consider the problem of visual representation learning for computational pathology, by exploiting large-scale image-text pairs gathered from public resources, alo…

cs.CL2024★ 7 cited

Towards Building Multilingual Language Model for Medicine

Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang +5

The development of open-source, multilingual medical language models can benefit a wide, linguistically diverse audience from different regions. To promote this domain, we present…

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