activity
20162026
most citedContrastive Learning of Medical Visual Representations from Paired Images and Text

281 citations · 475 across the 19 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

cs.CL2020★ 15 cited

Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation

Yasuhide Miura, Yuhao Zhang, Emily Bao Tsai +2

Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying po…

cs.CV2020★ 281 cited

Contrastive Learning of Medical Visual Representations from Paired Images and Text

Yuhao Zhang, Hang Jiang, Yasuhide Miura +2

Learning visual representations of medical images (e.g., X-rays) is core to medical image understanding but its progress has been held back by the scarcity of human annotations. Ex…

cs.CL2020

Do Syntax Trees Help Pre-trained Transformers Extract Information?

Devendra Singh Sachan, Yuhao Zhang, Peng Qi +1

Much recent work suggests that incorporating syntax information from dependency trees can improve task-specific transformer models. However, the effect of incorporating dependency…

cs.CL2020★ 16 cited

Biomedical and Clinical English Model Packages in the Stanza Python NLP Library

Yuhao Zhang, Yuhui Zhang, Peng Qi +2

We introduce biomedical and clinical English model packages for the Stanza Python NLP library. These packages offer accurate syntactic analysis and named entity recognition capabil…

cs.CL2020

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Peng Qi, Yuhao Zhang, Yuhui Zhang +2

We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages. Compared to existing widely used toolkits, Stanza features a language-…

cs.CL2020★ 3 cited

Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversations

Peng Qi, Yuhao Zhang, Christopher D. Manning

We investigate the problem of generating informative questions in information-asymmetric conversations. Unlike previous work on question generation which largely assumes knowledge…