A Framework for Cost-Effective and Self-Adaptive LLM Shaking and Recovery Mechanism

arXiv:2403.07283v1 Announce Type: cross
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 …

abstract applications arxiv cloud cloud services concerns cost cs.cl cs.cr cs.lg deploy domains framework language language models large language large language models llm llms privacy recovery services success through trade type world