arXiv ·
MBZUAI researchers have introduced MIRA, a novel framework for improving the factual accuracy of multimodal large language models in medical applications. MIRA uses calibrated retrieval to manage factual risk and integrates image embeddings with a medical knowledge base for efficient reasoning. Evaluated on medical VQA and report generation benchmarks, MIRA achieves state-of-the-art results, with code available on GitHub.
arXiv ·
The Symposium on Data Mining and Applications (SDMA 2014) was organized by MEGDAM to foster collaboration among data mining and machine learning researchers in Saudi Arabia, GCC countries, and the Middle East. The symposium covered areas such as statistics, computational intelligence, pattern recognition, databases, Big Data Mining and visualization. Acceptance was based on originality, significance and quality of contribution.
KAUST ·
KAUST alumna Haleema Alamri, a 2016 Ph.D. graduate in Physical Science and Engineering, was nominated to join the Ibn Khaldun Fellowship at MIT as a postdoctoral fellow, after joining Saudi Aramco as a research scientist. During her fellowship, she conducted research in chemistry and polymer science. Alamri participated in the Innovation to Impact forum during Crown Prince Mohammed bin Salman's visit to MIT in 2018. Why it matters: This highlights KAUST's role in developing Saudi female scientists and contributing to Saudi Vision 2030 through advanced research and international collaborations.