Survey explores collaborative AI: Large and small models working together

A new survey paper explores the synergistic collaboration between large language models (LLMs) and smaller, domain-specific models. This approach aims to enhance LLM adaptability to private domains while addressing challenges related to data privacy, model security, and resource limitations. The paper categorizes research into downward knowledge transfer (LLM to small model), upward knowledge transfer (small model to LLM), and inference-time collaboration, proposing a multi-objective optimization framework for practical deployment. AI

IMPACT This research could lead to more efficient and privacy-preserving AI deployments by enabling better collaboration between large and small models.

RANK_REASON This is a survey paper on a research topic. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Bingjie Yan
• large language models

• paper
• model release

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