Model description
We propose a task that aims to enable data-efficient and fast updates to KG embeddings without damaging the performance of the rest. We provide four experimental edit object models of the PT-KGE in the paper experiments used.
How to use
Here is how to use this model:
>>> from transformers import BertForMaskedLM
>>> model = BertForMaskedLM.from_pretrained(pretrained_model_name_or_path="zjunlp/KGEditor", subfolder="E-FB15k237")
BibTeX entry and citation info
@article{DBLP:journals/corr/abs-2301-10405,
author = {Siyuan Cheng and
Ningyu Zhang and
Bozhong Tian and
Zelin Dai and
Feiyu Xiong and
Wei Guo and
Huajun Chen},
title = {Editing Language Model-based Knowledge Graph Embeddings},
journal = {CoRR},
volume = {abs/2301.10405},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2301.10405},
doi = {10.48550/arXiv.2301.10405},
eprinttype = {arXiv},
eprint = {2301.10405},
timestamp = {Thu, 26 Jan 2023 17:49:16 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2301-10405.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}