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k-NN as a Popular Retrieval-Based External Memory Method
The -nearest neighbors (-NN) algorithm is a popular retrieval-based method for implementing external memory. It operates by creating a datastore of key-value pairs, with each pair representing a specific context state. The concept of 'context' is flexible and not restricted to a single sequence's history; it can be as broad as an entire dataset. This allows for retrieving the most relevant context from a large collection of sequences, not just the current one. When presented with a new query, the model uses -NN to find the most similar context representations from the datastore to enhance its predictions.
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References
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Reference of Foundations of Large Language Models Course
Tags
Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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k-NN as a Popular Retrieval-Based External Memory Method
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