SwiftKV: Understanding the Principles of Next-Generation KV Cache Compression for Maximizing LLM Inference Efficiency
At their core, Large Language Models (LLMs) are auto-regressive models that predict the next token based on preceding ones. This inherent characteristic leads to a structural problem: every time a new token is generated,
LLMKV CacheSwiftKVMemory Optimization+2