Multi Modal Query

Multi-modal query processing focuses on retrieving information from diverse data sources (text, images, sensor data) using queries that combine multiple modalities. Current research emphasizes developing efficient and effective retrieval models, often leveraging transformer architectures and large language models, to handle the complexities of cross-modal interactions and integrate information from different sources. This area is significant for improving knowledge retrieval in various applications, from enhancing search engines and autonomous driving systems to facilitating more nuanced analysis of unstructured data in fields like healthcare and fashion. The development of robust and scalable multi-modal query systems promises to unlock valuable insights from increasingly complex datasets.