핵심 개념
GEMEL is a generative framework that leverages Large Language Models to enhance Multimodal Entity Linking efficiently.
통계
"With only ∼0.3% of the model parameters fine-tuned, GEMEL achieves state-of-the-art results on two well-established MEL datasets."
"GEMEL exhibits high parameter efficiency and strong scalability."
"GEMEL outperforms all other approaches and achieves state-of-the-art performance on both MEL datasets."
인용구
"Multimodal Entity Linking has attracted increasing attention in the natural language processing community."
"GEMEL can leverage the capabilities of LLMs from large-scale pre-training to directly generate corresponding entity names."