Hongmei Fei

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

A parameter-efficient large model adaptation framework that integrates retrieval-augmented semantic conditioning modeling with distribution-imbalance-aware contrastive representation learning for agricultural pest and disease text entity recognition is proposed, offering an efficient and scalable pathway for adapting l...