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 ...

Abstract: Detecting land cover changes from multitemporal and multimodal remote sensing images acquired by different sensors at the same location is a complex yet highly valuable task. Recently, ...

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: In order to minimize the impact of influenza on public health, accurate early forecasting is essential. Various deep-learning-based models have been proposed to predict future influenza ...