An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

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 ...

If you want a new method to help you study better, NotebookLM helps turn your lecture notes into flashcards, quizzes, and ...

LLaVA-OneVision-1.5-RL introduces a training recipe for multimodal reinforcement learning, building upon the foundation of LLaVA-OneVision-1.5. This framework is designed to democratize access to ...

French AI startup Mistral launched its new Mistral 3 family of open-weight models on Tuesday, a launch that aims to prove it can lead in making AI publicly available and serve business clients better ...

Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning. The ...

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.

Abstract: The design of effective multimodal feature fusion strategies is the key task for multimodal learning, which often requires huge computational costs with extensive expertise. In this paper, ...

1 Department of Neuroscience, Institute of Psychopathology, Rome, Italy. 2 Department of Computer Engineering (AI), University of Genova, Genova, Italy. Accurately predicting individual responses to ...

Embedding models act as bridges between different data modalities by encoding diverse multimodal information into a shared dense representation space. There have been advancements in embedding models ...