SMALLM: a local small model augmented a cloud-based large language model for chinese named entity recognition in low-resource industries

Abstract Although the cloud-based commercial Large Language Models (LLMs) have achieved state-of-the-art (SOTA) performances and cutting-edge zero-shot learning abilities on a variety of Natural Language Processing (NLP) tasks, their performance on Named Entity Recognition (NER) is still significant...

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Autori principali:	Jinning Yang, Zhile Yang, Chengke Wu, Yuanjun Guo, Xiao Li, Jiarui Lin
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Springer 2025-09-01
Serie:	Complex & Intelligent Systems
Soggetti:	Chinese named entity recognition Large language model Low-resource
Accesso online:	https://doi.org/10.1007/s40747-025-02074-6
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