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CompressKV Enhances Resource Efficiency for Long-Context LLM Inference
CompressKV introduces semantic-retrieval-guided compression of key-value caches to reduce memory and decoding costs in long-context LLM inference. It addresses limitations of heuristic token eviction by considering attention head functionalities.
Reducing the memory footprint and decoding cost of KV caches enables more sustainable deployment of large language models on resource-constrained hardware. This approach improves efficiency without compromising the model's long-context capabilities.
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Score 78
Source Type arxiv
Reposts 0
Topic Quality 52
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