Multimodal Query

Multimodal query processing focuses on retrieving information from diverse data sources (text, images, audio, video) using queries that combine multiple modalities. Current research emphasizes developing models that effectively integrate these modalities, often leveraging vision-language models and graph networks, to improve retrieval accuracy and handle complex, nuanced queries. This area is significant because it advances information retrieval beyond text-only searches, enabling more intuitive and powerful interactions with large, heterogeneous datasets, with applications ranging from improved search engines to more sophisticated robot navigation. Challenges remain in addressing model oversensitivity to certain query combinations and ensuring robust performance across diverse data types.