Integrating k-NN Memory with Local Memory in Attention
To enhance the attention mechanism for a given query , language models aim to utilize both the immediate local memory, such as the standard Key-Value (KV) cache of recent tokens denoted as , and the long-term memory retrieved via -nearest neighbors, denoted as . Strategies to integrate these two sources of information include combining them to form a single, unified KV cache, , and applying standard QKV attention, or using and in separate, distinct attention steps.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Related
k-NN Memory Retrieval
Integrating k-NN Memory with Local Memory in Attention
Populating a k-NN Datastore for Language Modeling
Equivalence Between k-NN and Sparse Attention Models
k-NN Language Modeling (k-NN LM)
Vector Database
A language model is designed to be a question-answering assistant for a large corporate knowledge base containing thousands of separate project documents. A user asks a question about 'Project Alpha,' but the most relevant technical detail needed to answer it is located in a document for 'Project Zeta,' a completely unrelated past project. Which statement best explains the unique advantage of using a k-nearest neighbors (k-NN) based external memory system in this scenario?
Analyzing Long-Range Consistency in Language Models
In a k-NN based external memory system, the datastore of key-value pairs is limited to representing only the context states from the current, single sequence being processed.
Learn After
Combined KV Cache for k-NN and Local Memory
k-NN Search Augmented Attention
Optimizing Attention for a Specialized Chatbot
A team is designing a language model for a legal chatbot. The model must be able to follow the immediate flow of a user's query while also referencing specific, relevant legal precedents from a massive, static database. Which of the following approaches for the model's attention mechanism best addresses this dual requirement?
Diagnosing Memory Deficiencies in a Chatbot
Linear Combination of Local and External Attention