Yi, S., Lim, J., & Yoon, J. (2024). ProtocoLLM: Automatic Evaluation Framework of LLMs on Domain-Specific Scientific Protocol Formulation Tasks. arXiv preprint arXiv:2410.04601.
This paper introduces ProtocoLLM, a framework designed to automatically evaluate the ability of LLMs to generate executable scientific protocols. The authors aim to address the limitations of existing evaluation methods that rely on human evaluation or statistical scoring metrics, which are often poorly correlated with human judgment.
ProtocoLLM employs a three-step process:
ProtocoLLM and LLAM-EVAL provide a valuable contribution to the field of LLM evaluation, particularly for domain-specific tasks like scientific protocol formulation. The framework's flexibility, automation, and use of domain knowledge offer advantages over existing methods. The authors also introduce BIOPROT 2.0, a dataset of biology protocols and corresponding pseudocode, as a resource for further research and development in this area.
This research is significant as it addresses the need for robust and automated evaluation methods for LLMs in specialized domains like scientific research. The development of ProtocoLLM and LLAM-EVAL contributes to the advancement of LLM capabilities and their application in automating complex scientific tasks.
The authors acknowledge limitations such as the predefined actions may not be exhaustive, and the evaluation is limited to biology protocols. Future research could explore expanding the action set, evaluating LLMs in other scientific domains, and comparing LLAM-EVAL with other LLM-based evaluation methods.
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by Seungjun Yi,... um arxiv.org 10-08-2024
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