2025
LLMProto: A Hardware-Efficient Finetuning Model for Few-Shot Relation Extraction with Large Language Model
ICASSP 2025accepted
Recent studies have demonstrated that supervised fine-tuning of Large Language Models (LLMs) can significantly enhance performance across various Information Extraction (IE) tasks. However, the critical IE task of Relation Extraction (RE) faces substantial cost barriers in the supervised fine-tuning…