Papers by Utkarsh Saxena

    1 papers
    Eigen Attention: Attention in Low-Rank Space for KV Cache Compression (2024.findings-emnlp)

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    Challenge: Large language models (LLMs) have been increasing context lengths to enhance their performance, but at long context length, the KV cache becomes the new bottleneck in memory usage during inference.
    Approach: They propose an approach which performs the attention operation in a low-rank space and reduces the KV cache memory overhead.
    Outcome: The proposed approach reduces the KV cache memory overhead and reduces memory usage with minimal drop in performance over OPT, MPT, and Llama model families.

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