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cs.CL2024
Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion
Yang Liu, Xiaobin Tian, Zequn Sun +1
Traditional knowledge graph (KG) completion models learn embeddings to predict missing facts. Recent works attempt to complete KGs in a text-generation manner with large language m…
cs.CL2024
KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
Xindi Luo, Zequn Sun, Jing Zhao +2
Parameter-efficient finetuning (PEFT) is a key technique for adapting large language models (LLMs) to downstream tasks. In this paper, we study leveraging knowledge graph embedding…