The rapid progress of large language models (LLMs) has catalyzed the emergence of multimodal large language models (MLLMs) that unify visual understanding and image generation within a single ...

We present Magma, a foundation model that serves multimodal AI agentic tasks in both the digital and physical worlds. Magma is a significant extension of vision-language (VL) models in that it not ...

As large language models (LLMs) evolve into multimodal systems that can handle text, images, voice and code, they’re also becoming powerful orchestrators of external tools and connectors. With this ...

Although Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across diverse tasks, they encounter challenges in terms of reasoning efficiency, large model size and ...

Abstract: Most existing multimodal point-view fusion models for 3-D shape recognition typically improve recognition accuracy through complex feature fusion mechanisms. However, these mechanisms ...

The Allen Institute for AI, also known as Ai2, last week released Molmo 2, its latest multimodel suite capable of precise spatial and temporal understanding of video, image, and multi-image sets.

LINCOLN, Neb. (KOLN) - The StarTran Multi-modal Transportation Center received an Excellence in Unbuilt Architecture Honor Award for the project’s concept and presentation, Lincoln Transportation and ...

1 Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, Republic of Korea 2 Department of Systems Management Engineering, Sungkyunkwan University, Suwon, Republic of Korea ...

The model with the best C-index performance was deployed as a web-based risk calculator. Additionally, we assessed other performance indicators of the best-performing model, including the area under ...

Abstract: Adverse weather conditions like rain, fog, and snow significantly hinder perception in autonomous driving systems. This paper proposes a multimodal contrastive learning and transfer learning ...