Language and Cognition
Components of Language
Language Development
Higher Mental Functions of the Brain: Language
Language
Lateralization
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Updated: Apr 4, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Akila Kadambi1, Lisa Aziz-Zadeh2, Antonio Damasio3
1Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Brain and Creativity Institute, University of Southern California, Los Angeles, CA, USA; UCLA-CDU Dana Center for Neuroscience & Society, Los Angeles, CA, USA; USC Mrs. T.H. Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA; Semel Institute for Neuroscience and Behavior, UCLA, Los Angeles, CA, USA; Brain Research Institute, UCLA, Los Angeles, CA, USA.
Multimodal large language models (MLLMs) need internal and external embodiment to improve real-world interactions. A dual-embodied framework models these interactions, bridging data and experience for advanced AI.
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