4 papers
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…
ViLBias: Detecting and Reasoning about Bias in Multimodal Content
Shaina Raza, Caesar Saleh, Azib Farooq +11
Detecting bias in multimodal news requires models that reason over text--image pairs, not just classify text. In response, we present ViLBias, a VQA-style benchmark and framework f…
Benchmarking Vision-Language Contrastive Methods for Medical Representation Learning
Shuvendu Roy, Yasaman Parhizkar, Franklin Ogidi +5
We perform a comprehensive benchmarking of contrastive frameworks for learning multimodal representations in the medical domain. Through this study, we aim to answer the following…