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Anton Schwaighofer

3 accepted papers

2023

Exploring the Boundaries of GPT-4 in Radiology

EMNLP 2023long main

The recent success of general-domain large language models (LLMs) has significantly changed the natural language processing paradigm towards a unified foundation model across domains and applications. In this paper, we focus on assessing the performance of GPT-4, the most capable LLM so far, on the…

Cited by 0SourceScholar
2023

Learning To Exploit Temporal Structure for Biomedical Vision-Language Processing

CVPR 2023poster

Self-supervised learning in vision--language processing (VLP) exploits semantic alignment between imaging and text modalities. Prior work in biomedical VLP has mostly relied on the alignment of single image and report pairs even though clinical notes commonly refer to prior images. This does not onl…

Cited by 139SourcePDFScholar
2022

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

ECCV 2022poster

"Multi-modal data abounds in biomedicine, such as radiology images and reports. Interpreting this data at scale is essential for improving clinical care and accelerating clinical research. Biomedical text with its complex semantics poses additional challenges in vision-language modelling compared to…