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A Framework for Cost-Effective and Self-Adaptive LLM Shaking and Recovery Mechanism
March 13, 2024, 4:11 a.m. | Zhiyu Chen, Yu Li, Suochao Zhang, Jingbo Zhou, Jiwen Zhou, Chenfu Bao, Dianhai Yu
cs.CR updates on arXiv.org arxiv.org
Abstract: As Large Language Models (LLMs) gain great success in real-world applications, an increasing number of users are seeking to develop and deploy their customized LLMs through cloud services. Nonetheless, in some specific domains, there are still concerns regarding cost and trade-offs between privacy issues and accuracy. In this study, we introduce a cost-effective and self-adaptive LLM shaking tuning and recovery mechanism, named CypherTalk. With carefully designed horizontal and vertical shaking operators, we can achieve comparable …
applications arxiv cloud cloud services cost cost-effective cs.cl cs.cr cs.lg deploy domains framework great language language models large llm llms mechanism privacy real recovery services trade trade-offs world
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