Verbesserung der Darstellung von Beziehungen mit Multi-View Decoupling Learning in niedrig-ressourcenbasierten Prompt-basierten Ansätzen
MVRE verbessert die Darstellung von Beziehungen in niedrig-ressourcenbasierten Prompt-basierten Ansätzen durch Multi-View Decoupling Learning.
Few-shot Relation Extraction with CoT-ER Approach
Large language models can effectively perform few-shot relation extraction tasks with the CoT-ER approach, outperforming fully-supervised methods.
Retrieval-Augmented Generation-based Relation Extraction: Enhancing Performance through Relevant Sentence Integration
Retrieval-Augmented Generation-based Relation Extraction (RAG4RE) approach can outperform traditional Relation Extraction methods by integrating relevant example sentences into the prompt, mitigating hallucination issues in Large Language Models.
Improving Relation Extraction with End-to-End Trainable Retrieval-Augmented Generation (ETRAG)
This research paper introduces ETRAG, a novel approach for relation extraction that enhances retrieval-augmented generation by enabling end-to-end training of the retriever, leading to improved performance, especially in low-resource settings.
