Knowledge Graph Fusion for Language Model Fine-tuning. (arXiv:2206.14574v1 [cs.CL])

Language Models such as BERT have grown in popularity due to their ability to
be pre-trained and perform robustly on a wide range of Natural Language
Processing tasks. Often seen as an evolution over traditional word embedding
techniques, they can produce semantic representations of text, useful for tasks
such as semantic similarity. However, state-of-the-art models often have high
computational requirements and lack global context or domain knowledge which is
required for complete language understanding. To address these limitations, we
investigate …

arxiv fine-tuning fusion graph knowledge knowledge graph language language model model fine-tuning