SCA: Selective Compression Attention for Efficiently Extending the Context Window of Large Language Models (2024.findings-emnlp)
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| Challenge: | Existing methods to compress the KV cache of large language models are expensive and limited in their context window and cost. |
| Approach: | They propose a method to expand the context window and reduce memory footprint by compressing the KV cache of large language models. |
| Outcome: | The proposed method can reduce memory footprint and expand context window of large language models without training. |
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