Query Embeddings

Query embeddings are vector representations of search queries used to improve information retrieval and related tasks across diverse data modalities, including text, video, and point clouds. Current research focuses on enhancing embedding quality through techniques like iterative refinement with large language models, developing more efficient and generalizable architectures (e.g., late-interaction models, transformers), and adapting embeddings for complex queries involving Boolean logic or n-ary relations. These advancements are significantly impacting fields like multimedia retrieval, knowledge graph reasoning, and 3D scene understanding by enabling more accurate, efficient, and flexible information access and processing.