Adaptive Selection for Homogeneous Tools: An Instantiation in the RAG Scenario
- URL: http://arxiv.org/abs/2406.12429v2
- Date: Thu, 11 Jul 2024 04:37:47 GMT
- Title: Adaptive Selection for Homogeneous Tools: An Instantiation in the RAG Scenario
- Authors: Feiteng Mu, Yong Jiang, Liwen Zhang, Chu Liu, Wenjie Li, Pengjun Xie, Fei Huang,
- Abstract summary: Current research on tool learning primarily focuses on selecting the most effective tool from a wide array of options, often overlooking cost-effectiveness.
In this paper, we address the selection of homogeneous tools by predicting both their performance and the associated cost required to accomplish a given task.
- Score: 62.615210194004106
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Current research on tool learning primarily focuses on selecting the most effective tool from a wide array of options, often overlooking cost-effectiveness, a crucial factor in human problem-solving. In this paper, we address the selection of homogeneous tools by predicting both their performance and the associated cost required to accomplish a given task. We then assign queries to the optimal tools in a cost-effective manner. Our experimental results demonstrate that our method achieves higher performance at a lower cost compared to strong baseline approaches.
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