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October 3, 20250 citationsOpen Access

Efficient KV Cache Compression Using Composite Tokens for Language Models

KVCompose: Efficient Structured KV Cache Compression with Composite Tokens

Authors

Proposed method improves memory efficiency in long-context language models, suggesting better scalability.

Significant memory reduction achieved with composite tokens, while maintaining accuracy in long-context inference.
Attention-guided method effectively estimates token importance and adapts retention budgets across layers for efficiency.
Compatible with existing inference engines, enhancing practical deployment of language models without substantial restructuring.
Outperforms prior structured and semi-structured KV cache compression methods, addressing long-context limitations.

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Akulov et al. (2025) studied this question.

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October 3, 20250 citationsOpen Access

KVCompose: Efficient Structured KV Cache Compression with Composite Tokens

Authors

Proposed method improves memory efficiency in long-context language models, suggesting better scalability.

Significant memory reduction achieved with composite tokens, while maintaining accuracy in long-context inference.
Attention-guided method effectively estimates token importance and adapts retention budgets across layers for efficiency.
Compatible with existing inference engines, enhancing practical deployment of language models without substantial restructuring.
Outperforms prior structured and semi-structured KV cache compression methods, addressing long-context limitations.

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Bookmark

View Full Paper

Akulov et al. (2025) studied this question.

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Helpful

Bookmark

View Full Paper