Papers with memory savings

1 papers
500xCompressor: Generalized Prompt Compression for Large Language Models (2025.acl-long)

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Challenge: Prompt compression is important for large language models to increase inference speed, reduce computation cost, and improve user experience.
Approach: They propose a method that compresses natural language contexts into a special token . they propose to reduce computations and memory costs by reducing the complexity .
Outcome: The proposed method reduces computations and memory costs by 27-90% . it retains 70-74% and 77-84% of the LLM capabilities at high compression ratios .

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