Large Multimodal Model

Large multimodal models (LMMs) integrate vision and language processing capabilities to understand and generate information across multiple modalities. Current research focuses on improving LMM performance in complex tasks like temporal reasoning in videos, fine-grained image understanding, and robust handling of diverse data types, often leveraging architectures based on instruction tuning and contrastive learning. These advancements are significant for various applications, including improved intelligent tutoring systems, advanced robotics, and more accurate medical diagnoses, by enabling more sophisticated analysis and interaction with the world.