AAAI 2025technical0 citations
Stress-Testing of Multimodal Models in Medical Image-Based Report Generation
Flávia Carvalhido, Henrique Lopes Cardoso, Vítor Cerqueira
Abstract
Multimodal models, namely vision-language models, present unique possibilities through the seamless integration of different information mediums for data generation. These models mostly act as a black-box, making them lack transparency and explicability. Reliable results require accountable and trustworthy Artificial Intelligence (AI), namely when in use for critical tasks, such as the automatic generation of medical imaging reports for healthcare diagnosis. By exploring stress-testing techniques, multimodal generative models can become more transparent by disclosing their shortcomings, further supporting their responsible usage in the medical field.
BibTeX
@article{Carvalhido_Lopes Cardoso_Cerqueira_2025, title={Stress-Testing of Multimodal Models in Medical Image-Based Report Generation}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/35203}, DOI={10.1609/aaai.v39i28.35203}, abstractNote={Multimodal models, namely vision-language models, present unique possibilities through the seamless integration of different information mediums for data generation. These models mostly act as a black-box, making them lack transparency and explicability. Reliable results require accountable and trustworthy Artificial Intelligence (AI), namely when in use for critical tasks, such as the automatic generation of medical imaging reports for healthcare diagnosis. By exploring stress-testing techniques, multimodal generative models can become more transparent by disclosing their shortcomings, further supporting their responsible usage in the medical field.}, number={28}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Carvalhido, Flávia and Lopes Cardoso, Henrique and Cerqueira, Vítor}, year={2025}, month={Apr.}, pages={29251-29252} }