Structured reasoning with large language models for few-shot herbarium image classification

Herbarium image classification is challenging due to many factors, including limited sample sizes, the high diversity of plant morphologies, and variations in specimen placement. This paper explores the use of large language models (LLMs) to achieve high-accuracy herbarium image classification in fe...

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Bibliographic Details

Main Authors:	Yuyue Guo, Haibin Cai, Baihua Li, Gemma LC Bramley, Hannah J Atkins
Format:	Default Conference proceeding
Published:	2026
Subjects:	Herbarium image analysis Large language models Few-shot classification Structured reasoning
Online Access:	https://hdl.handle.net/2134/31056247.v1
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