11 citations · 28 across the 17 of their papers we have counts for
4 papers · 1 filter
Open-PMC-18M: A High-Fidelity Large Scale Medical Dataset for Multimodal Representation Learning
Negin Baghbanzadeh, Mohammed Saidul Islam, Sajad Ashkezari +2
In biomedical vision-language modeling, datasets are typically mined from scientific literature, pairing compound figures with captions that are short, context-dependent, and ofter…
Automated Capability Evaluation of Foundation Models
Arash Afkanpour, Omkar Dige, Fatemeh Tavakoli +3
Current evaluation frameworks for foundation models rely heavily on static, manually curated benchmarks, limiting their ability to capture the full breadth of model capabilities. T…
Advancing Medical Representation Learning Through High-Quality Data
Negin Baghbanzadeh, Adibvafa Fallahpour, Yasaman Parhizkar +8
Despite the growing scale of medical Vision-Language datasets, the impact of dataset quality on model performance remains under-explored. We introduce Open-PMC, a high-quality medi…
A Shared Encoder Approach to Multimodal Representation Learning
Shuvendu Roy, Franklin Ogidi, Ali Etemad +2
Multimodal representation learning has demonstrated remarkable potential in enabling models to process and integrate diverse data modalities, such as text and images, for improved…