Zhigang Li

A retrieval-augmented and distribution-imbalance-aware contrastive framework for low-resource agricultural pest and disease named entity recognition with large language models

Amid the rapid advancement of smart agriculture, a substantial volume of unstructured knowledge embedded in agricultural pest and disease texts urgently necessitates structured representation through high-quality named entity recognition. However, Chinese agricultural domain entities exhibit pronounced long-tail distri...