A bi-objective $\epsilon$-constrained framework for quality-cost optimization in language model ensembles

• URL: http://arxiv.org/abs/2312.16119v1
• Date: Tue, 26 Dec 2023 16:56:22 GMT
• Title: A bi-objective $\epsilon$-constrained framework for quality-cost optimization in language model ensembles
• Authors: Aditi Singla, Aditya Singh, Kanishk Kukreja
• Abstract summary: We propose an ensembling framework that uses diverse open-sourced Large Language Models (LLMs) to achieve high response quality while maintaining cost efficiency. We formulate a bi-objective optimization problem to represent the quality-cost tradeoff and then introduce an additional budget constraint that reduces the problem to a straightforward 0/1 knapsack problem.
• Score: 1.5039745292757671
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We propose an ensembling framework that uses diverse open-sourced Large Language Models (LLMs) to achieve high response quality while maintaining cost efficiency. We formulate a bi-objective optimization problem to represent the quality-cost tradeoff and then introduce an additional budget constraint that reduces the problem to a straightforward 0/1 knapsack problem. We empirically demonstrate that our framework outperforms the existing ensembling approaches in response quality while significantly reducing costs.

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