NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam

What are embeddings in the context of LLMs and how are they used in RAG pipelines?

Dense vector representations of text that capture semantic meaning; similar texts have high cosine similarity, enabling nearest-neighbor search for retrieval Compressed model weights stored in floating-point 16-bit format to reduce GPU memory usage Integer lookup tables mapping tokens to their positions in the vocabulary Sparse TF-IDF vectors used to score document relevance using keyword frequency

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Dense vector representations of text that capture semantic meaning; similar texts have high cosine similarity, enabling nearest-neighbor search for retrieval

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