Ergebnisse für: Multi-modal representations
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This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning i...
The rapid progress in the field of large multimodal foundation models, especially vision-language models, has dramatically transformed the landscape of machine learning, computer vision, and natural language processing. These powerful models, trained on vast amounts of multimodal data mixed with ima...
This book provides an overview of multiple aspects of spatial language understanding and explores recent trends of modeling based on very large foundational models and their applications.  The authors address the following five main themes: spatial semantic representations in both symbolic and ...
This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning i...
This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning i...
Constructing Representations to Learn in Science
Current research into student learning in science has shifted attention from the traditional cognitivist perspectives of conceptual change to socio-cultural and semiotic perspectives that characterize learning in terms of induction into disciplinary l...
This book provides an overview of multiple aspects of spatial language understanding and explores recent trends of modeling based on very large foundational models and their applications.  The authors address the following five main themes: spatial semantic representations in both symbolic and ...
The rapid progress in the field of large multimodal foundation models, especially vision-language models, has dramatically transformed the landscape of machine learning, computer vision, and natural language processing. These powerful models, trained on vast amounts of multimodal data mixed with ima...