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Leveraging Sparse Priming Representations for Efficient Learning
This chapter examines the role of semantic associations in large language models, introducing Sparse Priming Representations for efficient communication. It compares traditional training methods with in-context learning, emphasizing the advantages of utilizing associative capabilities.